{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "from itertools import product\n",
    "import statsmodels.api as sm\n",
    "from statsmodels.tsa.arima_model import ARIMA\n",
    "from datetime import datetime, timedelta\n",
    "import calendar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#取消科学计数法\n",
    "pd.set_option('display.float_format', lambda x: '%.3f' % x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "warnings.filterwarnings('ignore') #忽略警告\n",
    "plt.rcParams['font.sans-serif']=['SimHei'] #用来正常显示中文标签"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'encoding': 'GB2312', 'confidence': 0.99, 'language': 'Chinese'}"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#检查文件编码\n",
    "import chardet\n",
    "\n",
    "f = open('./mjm_002621.csv',mode='rb')\n",
    "data = f.read()\n",
    "chardet.detect(data)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>日期</th>\n",
       "      <th>股票代码</th>\n",
       "      <th>名称</th>\n",
       "      <th>收盘价</th>\n",
       "      <th>最高价</th>\n",
       "      <th>最低价</th>\n",
       "      <th>开盘价</th>\n",
       "      <th>前收盘</th>\n",
       "      <th>涨跌额</th>\n",
       "      <th>涨跌幅</th>\n",
       "      <th>换手率</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>总市值</th>\n",
       "      <th>流通市值</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2020-10-16</td>\n",
       "      <td>'002621</td>\n",
       "      <td>美吉姆</td>\n",
       "      <td>7.070</td>\n",
       "      <td>7.190</td>\n",
       "      <td>6.970</td>\n",
       "      <td>7.000</td>\n",
       "      <td>7.040</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.4261</td>\n",
       "      <td>0.575</td>\n",
       "      <td>4651108</td>\n",
       "      <td>33027211.880</td>\n",
       "      <td>5844506469.690</td>\n",
       "      <td>5721520645.260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2020-10-15</td>\n",
       "      <td>'002621</td>\n",
       "      <td>美吉姆</td>\n",
       "      <td>7.040</td>\n",
       "      <td>7.230</td>\n",
       "      <td>6.900</td>\n",
       "      <td>7.020</td>\n",
       "      <td>6.850</td>\n",
       "      <td>0.19</td>\n",
       "      <td>2.7737</td>\n",
       "      <td>0.774</td>\n",
       "      <td>6265798</td>\n",
       "      <td>44353038.570</td>\n",
       "      <td>5819706583.680</td>\n",
       "      <td>5697242622.720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2020-10-14</td>\n",
       "      <td>'002621</td>\n",
       "      <td>美吉姆</td>\n",
       "      <td>6.850</td>\n",
       "      <td>7.160</td>\n",
       "      <td>6.840</td>\n",
       "      <td>6.930</td>\n",
       "      <td>6.950</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>-1.4388</td>\n",
       "      <td>0.404</td>\n",
       "      <td>3267859</td>\n",
       "      <td>22796468.550</td>\n",
       "      <td>5662640638.950</td>\n",
       "      <td>5543481813.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2020-10-13</td>\n",
       "      <td>'002621</td>\n",
       "      <td>美吉姆</td>\n",
       "      <td>6.950</td>\n",
       "      <td>6.960</td>\n",
       "      <td>6.840</td>\n",
       "      <td>6.950</td>\n",
       "      <td>6.960</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.1437</td>\n",
       "      <td>0.228</td>\n",
       "      <td>1844460</td>\n",
       "      <td>12754077.980</td>\n",
       "      <td>5745306925.650</td>\n",
       "      <td>5624408555.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2020-10-12</td>\n",
       "      <td>'002621</td>\n",
       "      <td>美吉姆</td>\n",
       "      <td>6.960</td>\n",
       "      <td>6.990</td>\n",
       "      <td>6.720</td>\n",
       "      <td>6.990</td>\n",
       "      <td>6.860</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.4577</td>\n",
       "      <td>0.503</td>\n",
       "      <td>4071930</td>\n",
       "      <td>28129606.840</td>\n",
       "      <td>5753573554.320</td>\n",
       "      <td>5632501229.280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2191</th>\n",
       "      <td>2011-10-12</td>\n",
       "      <td>'002621</td>\n",
       "      <td>大连三垒</td>\n",
       "      <td>24.800</td>\n",
       "      <td>25.150</td>\n",
       "      <td>22.550</td>\n",
       "      <td>23.600</td>\n",
       "      <td>24.130</td>\n",
       "      <td>0.67</td>\n",
       "      <td>2.7766</td>\n",
       "      <td>30.192</td>\n",
       "      <td>6047448</td>\n",
       "      <td>145858448.750</td>\n",
       "      <td>2480000000.000</td>\n",
       "      <td>496744000.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2192</th>\n",
       "      <td>2011-10-11</td>\n",
       "      <td>'002621</td>\n",
       "      <td>大连三垒</td>\n",
       "      <td>24.130</td>\n",
       "      <td>25.850</td>\n",
       "      <td>23.700</td>\n",
       "      <td>24.250</td>\n",
       "      <td>23.600</td>\n",
       "      <td>0.53</td>\n",
       "      <td>2.2458</td>\n",
       "      <td>34.975</td>\n",
       "      <td>7005537</td>\n",
       "      <td>172370769.400</td>\n",
       "      <td>2413000000.000</td>\n",
       "      <td>483323900.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2193</th>\n",
       "      <td>2011-10-10</td>\n",
       "      <td>'002621</td>\n",
       "      <td>大连三垒</td>\n",
       "      <td>23.600</td>\n",
       "      <td>24.180</td>\n",
       "      <td>22.360</td>\n",
       "      <td>22.660</td>\n",
       "      <td>22.690</td>\n",
       "      <td>0.91</td>\n",
       "      <td>4.0106</td>\n",
       "      <td>22.776</td>\n",
       "      <td>4562109</td>\n",
       "      <td>106532465.000</td>\n",
       "      <td>2360000000.000</td>\n",
       "      <td>472708000.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2194</th>\n",
       "      <td>2011-09-30</td>\n",
       "      <td>'002621</td>\n",
       "      <td>大连三垒</td>\n",
       "      <td>22.690</td>\n",
       "      <td>23.800</td>\n",
       "      <td>22.050</td>\n",
       "      <td>23.100</td>\n",
       "      <td>24.080</td>\n",
       "      <td>-1.39</td>\n",
       "      <td>-5.7724</td>\n",
       "      <td>26.731</td>\n",
       "      <td>5354251</td>\n",
       "      <td>121509515.480</td>\n",
       "      <td>2269000000.000</td>\n",
       "      <td>454480700.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2195</th>\n",
       "      <td>2011-09-29</td>\n",
       "      <td>'002621</td>\n",
       "      <td>N三垒</td>\n",
       "      <td>24.080</td>\n",
       "      <td>25.150</td>\n",
       "      <td>22.880</td>\n",
       "      <td>23.980</td>\n",
       "      <td>24.000</td>\n",
       "      <td>0.08</td>\n",
       "      <td>0.3333</td>\n",
       "      <td>57.528</td>\n",
       "      <td>11522900</td>\n",
       "      <td>280662837.340</td>\n",
       "      <td>2408000000.000</td>\n",
       "      <td>482322400.000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2196 rows × 15 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              日期     股票代码    名称    收盘价    最高价    最低价    开盘价    前收盘    涨跌额  \\\n",
       "0     2020-10-16  '002621   美吉姆  7.070  7.190  6.970  7.000  7.040   0.03   \n",
       "1     2020-10-15  '002621   美吉姆  7.040  7.230  6.900  7.020  6.850   0.19   \n",
       "2     2020-10-14  '002621   美吉姆  6.850  7.160  6.840  6.930  6.950   -0.1   \n",
       "3     2020-10-13  '002621   美吉姆  6.950  6.960  6.840  6.950  6.960  -0.01   \n",
       "4     2020-10-12  '002621   美吉姆  6.960  6.990  6.720  6.990  6.860    0.1   \n",
       "...          ...      ...   ...    ...    ...    ...    ...    ...    ...   \n",
       "2191  2011-10-12  '002621  大连三垒 24.800 25.150 22.550 23.600 24.130   0.67   \n",
       "2192  2011-10-11  '002621  大连三垒 24.130 25.850 23.700 24.250 23.600   0.53   \n",
       "2193  2011-10-10  '002621  大连三垒 23.600 24.180 22.360 22.660 22.690   0.91   \n",
       "2194  2011-09-30  '002621  大连三垒 22.690 23.800 22.050 23.100 24.080  -1.39   \n",
       "2195  2011-09-29  '002621   N三垒 24.080 25.150 22.880 23.980 24.000   0.08   \n",
       "\n",
       "          涨跌幅    换手率       成交量          成交金额            总市值           流通市值  \n",
       "0      0.4261  0.575   4651108  33027211.880 5844506469.690 5721520645.260  \n",
       "1      2.7737  0.774   6265798  44353038.570 5819706583.680 5697242622.720  \n",
       "2     -1.4388  0.404   3267859  22796468.550 5662640638.950 5543481813.300  \n",
       "3     -0.1437  0.228   1844460  12754077.980 5745306925.650 5624408555.100  \n",
       "4      1.4577  0.503   4071930  28129606.840 5753573554.320 5632501229.280  \n",
       "...       ...    ...       ...           ...            ...            ...  \n",
       "2191   2.7766 30.192   6047448 145858448.750 2480000000.000  496744000.000  \n",
       "2192   2.2458 34.975   7005537 172370769.400 2413000000.000  483323900.000  \n",
       "2193   4.0106 22.776   4562109 106532465.000 2360000000.000  472708000.000  \n",
       "2194  -5.7724 26.731   5354251 121509515.480 2269000000.000  454480700.000  \n",
       "2195   0.3333 57.528  11522900 280662837.340 2408000000.000  482322400.000  \n",
       "\n",
       "[2196 rows x 15 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#数据加载\n",
    "data = pd.read_csv('./mjm_002621.csv', encoding='GB2312')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "#将日期作为data的索引\n",
    "data['日期'] = pd.to_datetime(data['日期'])\n",
    "data.index = data['日期'] "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>日期</th>\n",
       "      <th>股票代码</th>\n",
       "      <th>名称</th>\n",
       "      <th>收盘价</th>\n",
       "      <th>最高价</th>\n",
       "      <th>最低价</th>\n",
       "      <th>开盘价</th>\n",
       "      <th>前收盘</th>\n",
       "      <th>涨跌额</th>\n",
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       "      <th>成交量</th>\n",
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       "      <th>日期</th>\n",
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       "      <th></th>\n",
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       "    <tr>\n",
       "      <th>2020-10-16</th>\n",
       "      <td>2020-10-16</td>\n",
       "      <td>'002621</td>\n",
       "      <td>美吉姆</td>\n",
       "      <td>7.070</td>\n",
       "      <td>7.190</td>\n",
       "      <td>6.970</td>\n",
       "      <td>7.000</td>\n",
       "      <td>7.040</td>\n",
       "      <td>0.03</td>\n",
       "      <td>0.4261</td>\n",
       "      <td>0.575</td>\n",
       "      <td>4651108</td>\n",
       "      <td>33027211.880</td>\n",
       "      <td>5844506469.690</td>\n",
       "      <td>5721520645.260</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-15</th>\n",
       "      <td>2020-10-15</td>\n",
       "      <td>'002621</td>\n",
       "      <td>美吉姆</td>\n",
       "      <td>7.040</td>\n",
       "      <td>7.230</td>\n",
       "      <td>6.900</td>\n",
       "      <td>7.020</td>\n",
       "      <td>6.850</td>\n",
       "      <td>0.19</td>\n",
       "      <td>2.7737</td>\n",
       "      <td>0.774</td>\n",
       "      <td>6265798</td>\n",
       "      <td>44353038.570</td>\n",
       "      <td>5819706583.680</td>\n",
       "      <td>5697242622.720</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-14</th>\n",
       "      <td>2020-10-14</td>\n",
       "      <td>'002621</td>\n",
       "      <td>美吉姆</td>\n",
       "      <td>6.850</td>\n",
       "      <td>7.160</td>\n",
       "      <td>6.840</td>\n",
       "      <td>6.930</td>\n",
       "      <td>6.950</td>\n",
       "      <td>-0.1</td>\n",
       "      <td>-1.4388</td>\n",
       "      <td>0.404</td>\n",
       "      <td>3267859</td>\n",
       "      <td>22796468.550</td>\n",
       "      <td>5662640638.950</td>\n",
       "      <td>5543481813.300</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-13</th>\n",
       "      <td>2020-10-13</td>\n",
       "      <td>'002621</td>\n",
       "      <td>美吉姆</td>\n",
       "      <td>6.950</td>\n",
       "      <td>6.960</td>\n",
       "      <td>6.840</td>\n",
       "      <td>6.950</td>\n",
       "      <td>6.960</td>\n",
       "      <td>-0.01</td>\n",
       "      <td>-0.1437</td>\n",
       "      <td>0.228</td>\n",
       "      <td>1844460</td>\n",
       "      <td>12754077.980</td>\n",
       "      <td>5745306925.650</td>\n",
       "      <td>5624408555.100</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-12</th>\n",
       "      <td>2020-10-12</td>\n",
       "      <td>'002621</td>\n",
       "      <td>美吉姆</td>\n",
       "      <td>6.960</td>\n",
       "      <td>6.990</td>\n",
       "      <td>6.720</td>\n",
       "      <td>6.990</td>\n",
       "      <td>6.860</td>\n",
       "      <td>0.1</td>\n",
       "      <td>1.4577</td>\n",
       "      <td>0.503</td>\n",
       "      <td>4071930</td>\n",
       "      <td>28129606.840</td>\n",
       "      <td>5753573554.320</td>\n",
       "      <td>5632501229.280</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   日期     股票代码   名称   收盘价   最高价   最低价   开盘价   前收盘    涨跌额  \\\n",
       "日期                                                                         \n",
       "2020-10-16 2020-10-16  '002621  美吉姆 7.070 7.190 6.970 7.000 7.040   0.03   \n",
       "2020-10-15 2020-10-15  '002621  美吉姆 7.040 7.230 6.900 7.020 6.850   0.19   \n",
       "2020-10-14 2020-10-14  '002621  美吉姆 6.850 7.160 6.840 6.930 6.950   -0.1   \n",
       "2020-10-13 2020-10-13  '002621  美吉姆 6.950 6.960 6.840 6.950 6.960  -0.01   \n",
       "2020-10-12 2020-10-12  '002621  美吉姆 6.960 6.990 6.720 6.990 6.860    0.1   \n",
       "\n",
       "                涨跌幅   换手率      成交量         成交金额            总市值           流通市值  \n",
       "日期                                                                             \n",
       "2020-10-16   0.4261 0.575  4651108 33027211.880 5844506469.690 5721520645.260  \n",
       "2020-10-15   2.7737 0.774  6265798 44353038.570 5819706583.680 5697242622.720  \n",
       "2020-10-14  -1.4388 0.404  3267859 22796468.550 5662640638.950 5543481813.300  \n",
       "2020-10-13  -0.1437 0.228  1844460 12754077.980 5745306925.650 5624408555.100  \n",
       "2020-10-12   1.4577 0.503  4071930 28129606.840 5753573554.320 5632501229.280  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>收盘价</th>\n",
       "      <th>最高价</th>\n",
       "      <th>最低价</th>\n",
       "      <th>开盘价</th>\n",
       "      <th>前收盘</th>\n",
       "      <th>换手率</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>总市值</th>\n",
       "      <th>流通市值</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>日期</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-09-30</th>\n",
       "      <td>23.385</td>\n",
       "      <td>24.475</td>\n",
       "      <td>22.465</td>\n",
       "      <td>23.540</td>\n",
       "      <td>24.040</td>\n",
       "      <td>42.130</td>\n",
       "      <td>8438575.500</td>\n",
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       "      <td>2338500000.000</td>\n",
       "      <td>468401550.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-31</th>\n",
       "      <td>25.367</td>\n",
       "      <td>26.159</td>\n",
       "      <td>24.402</td>\n",
       "      <td>24.992</td>\n",
       "      <td>25.115</td>\n",
       "      <td>27.140</td>\n",
       "      <td>5436163.312</td>\n",
       "      <td>138331914.625</td>\n",
       "      <td>2536750000.000</td>\n",
       "      <td>508111025.000</td>\n",
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       "    <tr>\n",
       "      <th>2011-11-30</th>\n",
       "      <td>26.828</td>\n",
       "      <td>27.327</td>\n",
       "      <td>26.182</td>\n",
       "      <td>26.671</td>\n",
       "      <td>26.780</td>\n",
       "      <td>15.615</td>\n",
       "      <td>3127619.045</td>\n",
       "      <td>84215481.706</td>\n",
       "      <td>2682772727.273</td>\n",
       "      <td>537359377.273</td>\n",
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       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>22.895</td>\n",
       "      <td>23.502</td>\n",
       "      <td>22.569</td>\n",
       "      <td>23.111</td>\n",
       "      <td>23.248</td>\n",
       "      <td>8.104</td>\n",
       "      <td>1643899.273</td>\n",
       "      <td>39840843.355</td>\n",
       "      <td>2289454545.455</td>\n",
       "      <td>467519227.273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-31</th>\n",
       "      <td>20.243</td>\n",
       "      <td>20.699</td>\n",
       "      <td>19.757</td>\n",
       "      <td>20.177</td>\n",
       "      <td>20.199</td>\n",
       "      <td>4.495</td>\n",
       "      <td>1123700.600</td>\n",
       "      <td>22875662.247</td>\n",
       "      <td>2024333333.333</td>\n",
       "      <td>506083333.333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>7.218</td>\n",
       "      <td>7.332</td>\n",
       "      <td>7.144</td>\n",
       "      <td>7.239</td>\n",
       "      <td>7.238</td>\n",
       "      <td>0.382</td>\n",
       "      <td>2824821.950</td>\n",
       "      <td>19906333.920</td>\n",
       "      <td>5303056918.420</td>\n",
       "      <td>5191277072.827</td>\n",
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       "    <tr>\n",
       "      <th>2020-07-31</th>\n",
       "      <td>7.095</td>\n",
       "      <td>7.276</td>\n",
       "      <td>6.873</td>\n",
       "      <td>7.068</td>\n",
       "      <td>7.057</td>\n",
       "      <td>0.976</td>\n",
       "      <td>7896409.348</td>\n",
       "      <td>57169585.335</td>\n",
       "      <td>5864993332.046</td>\n",
       "      <td>5741576403.010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-08-31</th>\n",
       "      <td>7.286</td>\n",
       "      <td>7.463</td>\n",
       "      <td>7.122</td>\n",
       "      <td>7.261</td>\n",
       "      <td>7.277</td>\n",
       "      <td>1.059</td>\n",
       "      <td>8569866.905</td>\n",
       "      <td>63819294.215</td>\n",
       "      <td>6023223108.556</td>\n",
       "      <td>5896476553.723</td>\n",
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       "    <tr>\n",
       "      <th>2020-09-30</th>\n",
       "      <td>6.739</td>\n",
       "      <td>6.874</td>\n",
       "      <td>6.641</td>\n",
       "      <td>6.767</td>\n",
       "      <td>6.769</td>\n",
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       "      <td>5453726699.667</td>\n",
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       "    <tr>\n",
       "      <th>2020-10-31</th>\n",
       "      <td>6.955</td>\n",
       "      <td>7.093</td>\n",
       "      <td>6.805</td>\n",
       "      <td>6.937</td>\n",
       "      <td>6.867</td>\n",
       "      <td>0.530</td>\n",
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       "      <td>29949636.543</td>\n",
       "      <td>5749440239.985</td>\n",
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       "</table>\n",
       "<p>110 rows × 10 columns</p>\n",
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      ],
      "text/plain": [
       "              收盘价    最高价    最低价    开盘价    前收盘    换手率         成交量  \\\n",
       "日期                                                                 \n",
       "2011-09-30 23.385 24.475 22.465 23.540 24.040 42.130 8438575.500   \n",
       "2011-10-31 25.367 26.159 24.402 24.992 25.115 27.140 5436163.312   \n",
       "2011-11-30 26.828 27.327 26.182 26.671 26.780 15.615 3127619.045   \n",
       "2011-12-31 22.895 23.502 22.569 23.111 23.248  8.104 1643899.273   \n",
       "2012-01-31 20.243 20.699 19.757 20.177 20.199  4.495 1123700.600   \n",
       "...           ...    ...    ...    ...    ...    ...         ...   \n",
       "2020-06-30  7.218  7.332  7.144  7.239  7.238  0.382 2824821.950   \n",
       "2020-07-31  7.095  7.276  6.873  7.068  7.057  0.976 7896409.348   \n",
       "2020-08-31  7.286  7.463  7.122  7.261  7.277  1.059 8569866.905   \n",
       "2020-09-30  6.739  6.874  6.641  6.767  6.769  0.421 3403999.182   \n",
       "2020-10-31  6.955  7.093  6.805  6.937  6.867  0.530 4291013.333   \n",
       "\n",
       "                    成交金额            总市值           流通市值  \n",
       "日期                                                      \n",
       "2011-09-30 201086176.410 2338500000.000  468401550.000  \n",
       "2011-10-31 138331914.625 2536750000.000  508111025.000  \n",
       "2011-11-30  84215481.706 2682772727.273  537359377.273  \n",
       "2011-12-31  39840843.355 2289454545.455  467519227.273  \n",
       "2012-01-31  22875662.247 2024333333.333  506083333.333  \n",
       "...                  ...            ...            ...  \n",
       "2020-06-30  19906333.920 5303056918.420 5191277072.827  \n",
       "2020-07-31  57169585.335 5864993332.046 5741576403.010  \n",
       "2020-08-31  63819294.215 6023223108.556 5896476553.723  \n",
       "2020-09-30  23218949.166 5570956211.883 5453726699.667  \n",
       "2020-10-31  29949636.543 5749440239.985 5628454892.190  \n",
       "\n",
       "[110 rows x 10 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#按照月来统计\n",
    "data_month = data.resample('M').mean()\n",
    "data_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>2011-09-30</th>\n",
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       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>24.996</td>\n",
       "      <td>25.613</td>\n",
       "      <td>24.382</td>\n",
       "      <td>24.918</td>\n",
       "      <td>25.041</td>\n",
       "      <td>15.934</td>\n",
       "      <td>3199200.267</td>\n",
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       "      <td>503951761.667</td>\n",
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       "    <tr>\n",
       "      <th>2012-03-31</th>\n",
       "      <td>21.756</td>\n",
       "      <td>22.125</td>\n",
       "      <td>21.342</td>\n",
       "      <td>21.718</td>\n",
       "      <td>22.143</td>\n",
       "      <td>5.943</td>\n",
       "      <td>1485729.052</td>\n",
       "      <td>33526782.037</td>\n",
       "      <td>2215500000.000</td>\n",
       "      <td>553875000.000</td>\n",
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       "      <th>2012-06-30</th>\n",
       "      <td>13.854</td>\n",
       "      <td>14.137</td>\n",
       "      <td>13.537</td>\n",
       "      <td>13.819</td>\n",
       "      <td>13.860</td>\n",
       "      <td>7.284</td>\n",
       "      <td>2731622.441</td>\n",
       "      <td>39359952.746</td>\n",
       "      <td>2078161016.949</td>\n",
       "      <td>519540254.237</td>\n",
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       "    <tr>\n",
       "      <th>2012-09-30</th>\n",
       "      <td>11.348</td>\n",
       "      <td>11.617</td>\n",
       "      <td>11.072</td>\n",
       "      <td>11.352</td>\n",
       "      <td>11.385</td>\n",
       "      <td>6.072</td>\n",
       "      <td>2277026.985</td>\n",
       "      <td>26537567.730</td>\n",
       "      <td>1702269230.769</td>\n",
       "      <td>425567307.692</td>\n",
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       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>11.232</td>\n",
       "      <td>11.441</td>\n",
       "      <td>10.987</td>\n",
       "      <td>11.210</td>\n",
       "      <td>11.218</td>\n",
       "      <td>6.668</td>\n",
       "      <td>2500574.410</td>\n",
       "      <td>28568817.116</td>\n",
       "      <td>1684770491.803</td>\n",
       "      <td>421192622.951</td>\n",
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       "    <tr>\n",
       "      <th>2013-03-31</th>\n",
       "      <td>12.282</td>\n",
       "      <td>12.481</td>\n",
       "      <td>12.053</td>\n",
       "      <td>12.262</td>\n",
       "      <td>12.283</td>\n",
       "      <td>6.118</td>\n",
       "      <td>2294333.554</td>\n",
       "      <td>28483110.117</td>\n",
       "      <td>1842321428.571</td>\n",
       "      <td>460580357.143</td>\n",
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       "    <tr>\n",
       "      <th>2013-06-30</th>\n",
       "      <td>11.829</td>\n",
       "      <td>11.977</td>\n",
       "      <td>11.623</td>\n",
       "      <td>11.787</td>\n",
       "      <td>11.811</td>\n",
       "      <td>3.941</td>\n",
       "      <td>1477740.123</td>\n",
       "      <td>17814598.498</td>\n",
       "      <td>1774394736.842</td>\n",
       "      <td>443598684.211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-09-30</th>\n",
       "      <td>12.532</td>\n",
       "      <td>12.722</td>\n",
       "      <td>12.322</td>\n",
       "      <td>12.515</td>\n",
       "      <td>12.538</td>\n",
       "      <td>6.859</td>\n",
       "      <td>2572042.938</td>\n",
       "      <td>32519854.284</td>\n",
       "      <td>1879875000.000</td>\n",
       "      <td>469968750.000</td>\n",
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       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>13.158</td>\n",
       "      <td>13.369</td>\n",
       "      <td>12.906</td>\n",
       "      <td>13.110</td>\n",
       "      <td>13.132</td>\n",
       "      <td>6.750</td>\n",
       "      <td>2531093.672</td>\n",
       "      <td>34024468.549</td>\n",
       "      <td>1973754098.361</td>\n",
       "      <td>493438524.590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-03-31</th>\n",
       "      <td>14.531</td>\n",
       "      <td>14.776</td>\n",
       "      <td>14.259</td>\n",
       "      <td>14.507</td>\n",
       "      <td>14.519</td>\n",
       "      <td>5.201</td>\n",
       "      <td>1950262.759</td>\n",
       "      <td>28860756.481</td>\n",
       "      <td>2179577586.207</td>\n",
       "      <td>544894396.552</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-06-30</th>\n",
       "      <td>12.298</td>\n",
       "      <td>12.468</td>\n",
       "      <td>12.103</td>\n",
       "      <td>12.264</td>\n",
       "      <td>12.291</td>\n",
       "      <td>4.175</td>\n",
       "      <td>1971298.230</td>\n",
       "      <td>23370090.945</td>\n",
       "      <td>2208405737.705</td>\n",
       "      <td>552101434.426</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-09-30</th>\n",
       "      <td>11.682</td>\n",
       "      <td>11.852</td>\n",
       "      <td>11.477</td>\n",
       "      <td>11.635</td>\n",
       "      <td>11.621</td>\n",
       "      <td>6.134</td>\n",
       "      <td>3450551.323</td>\n",
       "      <td>40954571.780</td>\n",
       "      <td>2628450000.000</td>\n",
       "      <td>657112500.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>15.629</td>\n",
       "      <td>15.957</td>\n",
       "      <td>15.242</td>\n",
       "      <td>15.623</td>\n",
       "      <td>15.658</td>\n",
       "      <td>5.844</td>\n",
       "      <td>3287378.508</td>\n",
       "      <td>51730764.295</td>\n",
       "      <td>3516565573.770</td>\n",
       "      <td>879141393.443</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-03-31</th>\n",
       "      <td>14.454</td>\n",
       "      <td>14.630</td>\n",
       "      <td>14.176</td>\n",
       "      <td>14.355</td>\n",
       "      <td>14.362</td>\n",
       "      <td>4.600</td>\n",
       "      <td>2587456.105</td>\n",
       "      <td>38480914.563</td>\n",
       "      <td>3252039473.684</td>\n",
       "      <td>813009868.421</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-06-30</th>\n",
       "      <td>22.543</td>\n",
       "      <td>23.269</td>\n",
       "      <td>21.695</td>\n",
       "      <td>22.494</td>\n",
       "      <td>22.518</td>\n",
       "      <td>7.623</td>\n",
       "      <td>4288043.774</td>\n",
       "      <td>98068234.588</td>\n",
       "      <td>5072262096.774</td>\n",
       "      <td>1268065524.194</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-09-30</th>\n",
       "      <td>17.672</td>\n",
       "      <td>18.312</td>\n",
       "      <td>16.911</td>\n",
       "      <td>17.460</td>\n",
       "      <td>19.098</td>\n",
       "      <td>8.578</td>\n",
       "      <td>4824985.719</td>\n",
       "      <td>90413836.826</td>\n",
       "      <td>4301472656.250</td>\n",
       "      <td>1075368164.062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>23.566</td>\n",
       "      <td>23.996</td>\n",
       "      <td>23.011</td>\n",
       "      <td>23.501</td>\n",
       "      <td>23.517</td>\n",
       "      <td>5.548</td>\n",
       "      <td>3120869.213</td>\n",
       "      <td>74298096.964</td>\n",
       "      <td>5302254098.361</td>\n",
       "      <td>1325563524.590</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-03-31</th>\n",
       "      <td>17.249</td>\n",
       "      <td>17.705</td>\n",
       "      <td>16.731</td>\n",
       "      <td>17.294</td>\n",
       "      <td>17.341</td>\n",
       "      <td>3.916</td>\n",
       "      <td>2202749.322</td>\n",
       "      <td>38115666.434</td>\n",
       "      <td>3881021186.441</td>\n",
       "      <td>970255296.610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-06-30</th>\n",
       "      <td>16.114</td>\n",
       "      <td>16.370</td>\n",
       "      <td>15.758</td>\n",
       "      <td>15.990</td>\n",
       "      <td>19.295</td>\n",
       "      <td>4.609</td>\n",
       "      <td>2592749.820</td>\n",
       "      <td>49802455.971</td>\n",
       "      <td>4356000000.000</td>\n",
       "      <td>1089000000.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-09-30</th>\n",
       "      <td>10.150</td>\n",
       "      <td>10.339</td>\n",
       "      <td>9.920</td>\n",
       "      <td>10.090</td>\n",
       "      <td>21.727</td>\n",
       "      <td>2.088</td>\n",
       "      <td>1174479.062</td>\n",
       "      <td>25459274.042</td>\n",
       "      <td>4887914062.500</td>\n",
       "      <td>1279406250.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>21.740</td>\n",
       "      <td>22.325</td>\n",
       "      <td>21.159</td>\n",
       "      <td>21.608</td>\n",
       "      <td>25.787</td>\n",
       "      <td>1.744</td>\n",
       "      <td>3924273.450</td>\n",
       "      <td>108246551.449</td>\n",
       "      <td>5825175000.000</td>\n",
       "      <td>5825175000.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-03-31</th>\n",
       "      <td>27.532</td>\n",
       "      <td>27.989</td>\n",
       "      <td>27.151</td>\n",
       "      <td>27.547</td>\n",
       "      <td>27.586</td>\n",
       "      <td>0.630</td>\n",
       "      <td>1417999.695</td>\n",
       "      <td>39650575.217</td>\n",
       "      <td>6194669491.525</td>\n",
       "      <td>6194669491.525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-06-30</th>\n",
       "      <td>8.726</td>\n",
       "      <td>8.946</td>\n",
       "      <td>8.517</td>\n",
       "      <td>8.801</td>\n",
       "      <td>21.036</td>\n",
       "      <td>0.156</td>\n",
       "      <td>350855.983</td>\n",
       "      <td>8011239.558</td>\n",
       "      <td>5124412500.000</td>\n",
       "      <td>5124412500.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-09-30</th>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>15.190</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.000</td>\n",
       "      <td>5126625000.000</td>\n",
       "      <td>5126625000.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>11.053</td>\n",
       "      <td>11.283</td>\n",
       "      <td>10.748</td>\n",
       "      <td>11.015</td>\n",
       "      <td>15.351</td>\n",
       "      <td>0.891</td>\n",
       "      <td>3008531.067</td>\n",
       "      <td>47558485.452</td>\n",
       "      <td>5183043750.000</td>\n",
       "      <td>5183043750.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-03-31</th>\n",
       "      <td>5.665</td>\n",
       "      <td>5.794</td>\n",
       "      <td>5.550</td>\n",
       "      <td>5.650</td>\n",
       "      <td>15.756</td>\n",
       "      <td>0.210</td>\n",
       "      <td>708571.915</td>\n",
       "      <td>10537701.503</td>\n",
       "      <td>5309675847.458</td>\n",
       "      <td>5309675847.458</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-06-30</th>\n",
       "      <td>11.026</td>\n",
       "      <td>11.227</td>\n",
       "      <td>10.755</td>\n",
       "      <td>10.926</td>\n",
       "      <td>16.135</td>\n",
       "      <td>0.352</td>\n",
       "      <td>1187819.050</td>\n",
       "      <td>19179026.936</td>\n",
       "      <td>5475431250.000</td>\n",
       "      <td>5475431250.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-09-30</th>\n",
       "      <td>16.328</td>\n",
       "      <td>16.679</td>\n",
       "      <td>15.968</td>\n",
       "      <td>16.316</td>\n",
       "      <td>17.609</td>\n",
       "      <td>0.385</td>\n",
       "      <td>1301011.031</td>\n",
       "      <td>23351168.881</td>\n",
       "      <td>5955709385.156</td>\n",
       "      <td>5921753906.250</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>16.706</td>\n",
       "      <td>17.061</td>\n",
       "      <td>16.293</td>\n",
       "      <td>16.645</td>\n",
       "      <td>16.681</td>\n",
       "      <td>0.273</td>\n",
       "      <td>920558.683</td>\n",
       "      <td>15619327.573</td>\n",
       "      <td>5806980002.500</td>\n",
       "      <td>5638331250.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-03-31</th>\n",
       "      <td>21.618</td>\n",
       "      <td>21.897</td>\n",
       "      <td>21.121</td>\n",
       "      <td>21.469</td>\n",
       "      <td>21.497</td>\n",
       "      <td>0.805</td>\n",
       "      <td>2716379.845</td>\n",
       "      <td>60064205.478</td>\n",
       "      <td>7514224807.759</td>\n",
       "      <td>7295993534.483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-06-30</th>\n",
       "      <td>20.534</td>\n",
       "      <td>20.931</td>\n",
       "      <td>20.172</td>\n",
       "      <td>20.568</td>\n",
       "      <td>20.562</td>\n",
       "      <td>0.482</td>\n",
       "      <td>1728323.283</td>\n",
       "      <td>36378223.941</td>\n",
       "      <td>7712562643.842</td>\n",
       "      <td>7488762552.584</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-09-30</th>\n",
       "      <td>12.750</td>\n",
       "      <td>12.907</td>\n",
       "      <td>12.572</td>\n",
       "      <td>12.755</td>\n",
       "      <td>12.763</td>\n",
       "      <td>0.317</td>\n",
       "      <td>1818938.231</td>\n",
       "      <td>23139639.220</td>\n",
       "      <td>7533557213.310</td>\n",
       "      <td>7318619316.245</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>11.725</td>\n",
       "      <td>11.894</td>\n",
       "      <td>11.590</td>\n",
       "      <td>11.757</td>\n",
       "      <td>11.746</td>\n",
       "      <td>0.355</td>\n",
       "      <td>2054269.410</td>\n",
       "      <td>24236608.060</td>\n",
       "      <td>6928230792.428</td>\n",
       "      <td>6777756760.364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-03-31</th>\n",
       "      <td>10.966</td>\n",
       "      <td>11.172</td>\n",
       "      <td>10.714</td>\n",
       "      <td>10.938</td>\n",
       "      <td>10.974</td>\n",
       "      <td>0.711</td>\n",
       "      <td>4108919.879</td>\n",
       "      <td>45635105.967</td>\n",
       "      <td>6479626816.496</td>\n",
       "      <td>6338896004.483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-06-30</th>\n",
       "      <td>8.690</td>\n",
       "      <td>8.862</td>\n",
       "      <td>8.550</td>\n",
       "      <td>8.718</td>\n",
       "      <td>8.719</td>\n",
       "      <td>0.533</td>\n",
       "      <td>3289133.119</td>\n",
       "      <td>28615323.789</td>\n",
       "      <td>5486349313.590</td>\n",
       "      <td>5368343021.601</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-30</th>\n",
       "      <td>7.037</td>\n",
       "      <td>7.202</td>\n",
       "      <td>6.875</td>\n",
       "      <td>7.029</td>\n",
       "      <td>7.031</td>\n",
       "      <td>0.817</td>\n",
       "      <td>6613221.242</td>\n",
       "      <td>47968523.074</td>\n",
       "      <td>5817326796.639</td>\n",
       "      <td>5694912913.486</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>6.955</td>\n",
       "      <td>7.093</td>\n",
       "      <td>6.805</td>\n",
       "      <td>6.937</td>\n",
       "      <td>6.867</td>\n",
       "      <td>0.530</td>\n",
       "      <td>4291013.333</td>\n",
       "      <td>29949636.543</td>\n",
       "      <td>5749440239.985</td>\n",
       "      <td>5628454892.190</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              收盘价    最高价    最低价    开盘价    前收盘    换手率         成交量  \\\n",
       "日期                                                                 \n",
       "2011-09-30 23.385 24.475 22.465 23.540 24.040 42.130 8438575.500   \n",
       "2011-12-31 24.996 25.613 24.382 24.918 25.041 15.934 3199200.267   \n",
       "2012-03-31 21.756 22.125 21.342 21.718 22.143  5.943 1485729.052   \n",
       "2012-06-30 13.854 14.137 13.537 13.819 13.860  7.284 2731622.441   \n",
       "2012-09-30 11.348 11.617 11.072 11.352 11.385  6.072 2277026.985   \n",
       "2012-12-31 11.232 11.441 10.987 11.210 11.218  6.668 2500574.410   \n",
       "2013-03-31 12.282 12.481 12.053 12.262 12.283  6.118 2294333.554   \n",
       "2013-06-30 11.829 11.977 11.623 11.787 11.811  3.941 1477740.123   \n",
       "2013-09-30 12.532 12.722 12.322 12.515 12.538  6.859 2572042.938   \n",
       "2013-12-31 13.158 13.369 12.906 13.110 13.132  6.750 2531093.672   \n",
       "2014-03-31 14.531 14.776 14.259 14.507 14.519  5.201 1950262.759   \n",
       "2014-06-30 12.298 12.468 12.103 12.264 12.291  4.175 1971298.230   \n",
       "2014-09-30 11.682 11.852 11.477 11.635 11.621  6.134 3450551.323   \n",
       "2014-12-31 15.629 15.957 15.242 15.623 15.658  5.844 3287378.508   \n",
       "2015-03-31 14.454 14.630 14.176 14.355 14.362  4.600 2587456.105   \n",
       "2015-06-30 22.543 23.269 21.695 22.494 22.518  7.623 4288043.774   \n",
       "2015-09-30 17.672 18.312 16.911 17.460 19.098  8.578 4824985.719   \n",
       "2015-12-31 23.566 23.996 23.011 23.501 23.517  5.548 3120869.213   \n",
       "2016-03-31 17.249 17.705 16.731 17.294 17.341  3.916 2202749.322   \n",
       "2016-06-30 16.114 16.370 15.758 15.990 19.295  4.609 2592749.820   \n",
       "2016-09-30 10.150 10.339  9.920 10.090 21.727  2.088 1174479.062   \n",
       "2016-12-31 21.740 22.325 21.159 21.608 25.787  1.744 3924273.450   \n",
       "2017-03-31 27.532 27.989 27.151 27.547 27.586  0.630 1417999.695   \n",
       "2017-06-30  8.726  8.946  8.517  8.801 21.036  0.156  350855.983   \n",
       "2017-09-30  0.000  0.000  0.000  0.000 15.190  0.000       0.000   \n",
       "2017-12-31 11.053 11.283 10.748 11.015 15.351  0.891 3008531.067   \n",
       "2018-03-31  5.665  5.794  5.550  5.650 15.756  0.210  708571.915   \n",
       "2018-06-30 11.026 11.227 10.755 10.926 16.135  0.352 1187819.050   \n",
       "2018-09-30 16.328 16.679 15.968 16.316 17.609  0.385 1301011.031   \n",
       "2018-12-31 16.706 17.061 16.293 16.645 16.681  0.273  920558.683   \n",
       "2019-03-31 21.618 21.897 21.121 21.469 21.497  0.805 2716379.845   \n",
       "2019-06-30 20.534 20.931 20.172 20.568 20.562  0.482 1728323.283   \n",
       "2019-09-30 12.750 12.907 12.572 12.755 12.763  0.317 1818938.231   \n",
       "2019-12-31 11.725 11.894 11.590 11.757 11.746  0.355 2054269.410   \n",
       "2020-03-31 10.966 11.172 10.714 10.938 10.974  0.711 4108919.879   \n",
       "2020-06-30  8.690  8.862  8.550  8.718  8.719  0.533 3289133.119   \n",
       "2020-09-30  7.037  7.202  6.875  7.029  7.031  0.817 6613221.242   \n",
       "2020-12-31  6.955  7.093  6.805  6.937  6.867  0.530 4291013.333   \n",
       "\n",
       "                    成交金额            总市值           流通市值  \n",
       "日期                                                      \n",
       "2011-09-30 201086176.410 2338500000.000  468401550.000  \n",
       "2011-12-31  82375829.756 2499616666.667  503951761.667  \n",
       "2012-03-31  33526782.037 2215500000.000  553875000.000  \n",
       "2012-06-30  39359952.746 2078161016.949  519540254.237  \n",
       "2012-09-30  26537567.730 1702269230.769  425567307.692  \n",
       "2012-12-31  28568817.116 1684770491.803  421192622.951  \n",
       "2013-03-31  28483110.117 1842321428.571  460580357.143  \n",
       "2013-06-30  17814598.498 1774394736.842  443598684.211  \n",
       "2013-09-30  32519854.284 1879875000.000  469968750.000  \n",
       "2013-12-31  34024468.549 1973754098.361  493438524.590  \n",
       "2014-03-31  28860756.481 2179577586.207  544894396.552  \n",
       "2014-06-30  23370090.945 2208405737.705  552101434.426  \n",
       "2014-09-30  40954571.780 2628450000.000  657112500.000  \n",
       "2014-12-31  51730764.295 3516565573.770  879141393.443  \n",
       "2015-03-31  38480914.563 3252039473.684  813009868.421  \n",
       "2015-06-30  98068234.588 5072262096.774 1268065524.194  \n",
       "2015-09-30  90413836.826 4301472656.250 1075368164.062  \n",
       "2015-12-31  74298096.964 5302254098.361 1325563524.590  \n",
       "2016-03-31  38115666.434 3881021186.441  970255296.610  \n",
       "2016-06-30  49802455.971 4356000000.000 1089000000.000  \n",
       "2016-09-30  25459274.042 4887914062.500 1279406250.000  \n",
       "2016-12-31 108246551.449 5825175000.000 5825175000.000  \n",
       "2017-03-31  39650575.217 6194669491.525 6194669491.525  \n",
       "2017-06-30   8011239.558 5124412500.000 5124412500.000  \n",
       "2017-09-30         0.000 5126625000.000 5126625000.000  \n",
       "2017-12-31  47558485.452 5183043750.000 5183043750.000  \n",
       "2018-03-31  10537701.503 5309675847.458 5309675847.458  \n",
       "2018-06-30  19179026.936 5475431250.000 5475431250.000  \n",
       "2018-09-30  23351168.881 5955709385.156 5921753906.250  \n",
       "2018-12-31  15619327.573 5806980002.500 5638331250.000  \n",
       "2019-03-31  60064205.478 7514224807.759 7295993534.483  \n",
       "2019-06-30  36378223.941 7712562643.842 7488762552.584  \n",
       "2019-09-30  23139639.220 7533557213.310 7318619316.245  \n",
       "2019-12-31  24236608.060 6928230792.428 6777756760.364  \n",
       "2020-03-31  45635105.967 6479626816.496 6338896004.483  \n",
       "2020-06-30  28615323.789 5486349313.590 5368343021.601  \n",
       "2020-09-30  47968523.074 5817326796.639 5694912913.486  \n",
       "2020-12-31  29949636.543 5749440239.985 5628454892.190  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#按照季度来统计\n",
    "data_Q = data.resample('Q-DEC').mean()\n",
    "data_Q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>收盘价</th>\n",
       "      <th>最高价</th>\n",
       "      <th>最低价</th>\n",
       "      <th>开盘价</th>\n",
       "      <th>前收盘</th>\n",
       "      <th>换手率</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>总市值</th>\n",
       "      <th>流通市值</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>日期</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>24.944</td>\n",
       "      <td>25.576</td>\n",
       "      <td>24.321</td>\n",
       "      <td>24.873</td>\n",
       "      <td>25.009</td>\n",
       "      <td>16.779</td>\n",
       "      <td>3368212.371</td>\n",
       "      <td>86205195.777</td>\n",
       "      <td>2494419354.839</td>\n",
       "      <td>502804980.645</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-12-31</th>\n",
       "      <td>14.412</td>\n",
       "      <td>14.693</td>\n",
       "      <td>14.100</td>\n",
       "      <td>14.390</td>\n",
       "      <td>14.512</td>\n",
       "      <td>6.485</td>\n",
       "      <td>2254649.391</td>\n",
       "      <td>31828931.344</td>\n",
       "      <td>1911641975.309</td>\n",
       "      <td>477910493.827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2013-12-31</th>\n",
       "      <td>12.466</td>\n",
       "      <td>12.653</td>\n",
       "      <td>12.241</td>\n",
       "      <td>12.434</td>\n",
       "      <td>12.456</td>\n",
       "      <td>5.958</td>\n",
       "      <td>2234123.227</td>\n",
       "      <td>28433821.582</td>\n",
       "      <td>1869838235.294</td>\n",
       "      <td>467459558.824</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2014-12-31</th>\n",
       "      <td>13.492</td>\n",
       "      <td>13.719</td>\n",
       "      <td>13.229</td>\n",
       "      <td>13.464</td>\n",
       "      <td>13.479</td>\n",
       "      <td>5.353</td>\n",
       "      <td>2686450.437</td>\n",
       "      <td>36396421.270</td>\n",
       "      <td>2638726530.612</td>\n",
       "      <td>659681632.653</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2015-12-31</th>\n",
       "      <td>19.631</td>\n",
       "      <td>20.132</td>\n",
       "      <td>19.013</td>\n",
       "      <td>19.524</td>\n",
       "      <td>19.965</td>\n",
       "      <td>6.649</td>\n",
       "      <td>3739818.934</td>\n",
       "      <td>76198000.599</td>\n",
       "      <td>4502369877.049</td>\n",
       "      <td>1125592469.262</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2016-12-31</th>\n",
       "      <td>16.207</td>\n",
       "      <td>16.575</td>\n",
       "      <td>15.790</td>\n",
       "      <td>16.139</td>\n",
       "      <td>21.057</td>\n",
       "      <td>3.076</td>\n",
       "      <td>2453864.820</td>\n",
       "      <td>54962953.932</td>\n",
       "      <td>4741939549.180</td>\n",
       "      <td>2274862961.066</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2017-12-31</th>\n",
       "      <td>11.521</td>\n",
       "      <td>11.742</td>\n",
       "      <td>11.303</td>\n",
       "      <td>11.534</td>\n",
       "      <td>19.664</td>\n",
       "      <td>0.410</td>\n",
       "      <td>1168955.758</td>\n",
       "      <td>23252325.567</td>\n",
       "      <td>5398211065.574</td>\n",
       "      <td>5398211065.574</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2018-12-31</th>\n",
       "      <td>12.523</td>\n",
       "      <td>12.784</td>\n",
       "      <td>12.232</td>\n",
       "      <td>12.477</td>\n",
       "      <td>16.566</td>\n",
       "      <td>0.307</td>\n",
       "      <td>1035280.300</td>\n",
       "      <td>17300824.970</td>\n",
       "      <td>5643543007.407</td>\n",
       "      <td>5592958333.333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2019-12-31</th>\n",
       "      <td>16.516</td>\n",
       "      <td>16.764</td>\n",
       "      <td>16.227</td>\n",
       "      <td>16.498</td>\n",
       "      <td>16.503</td>\n",
       "      <td>0.483</td>\n",
       "      <td>2068814.947</td>\n",
       "      <td>35446422.111</td>\n",
       "      <td>7421647929.032</td>\n",
       "      <td>7219863918.415</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>8.756</td>\n",
       "      <td>8.935</td>\n",
       "      <td>8.574</td>\n",
       "      <td>8.753</td>\n",
       "      <td>8.763</td>\n",
       "      <td>0.687</td>\n",
       "      <td>4733306.291</td>\n",
       "      <td>40638944.930</td>\n",
       "      <td>5915096163.369</td>\n",
       "      <td>5788482477.131</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              收盘价    最高价    最低价    开盘价    前收盘    换手率         成交量         成交金额  \\\n",
       "日期                                                                              \n",
       "2011-12-31 24.944 25.576 24.321 24.873 25.009 16.779 3368212.371 86205195.777   \n",
       "2012-12-31 14.412 14.693 14.100 14.390 14.512  6.485 2254649.391 31828931.344   \n",
       "2013-12-31 12.466 12.653 12.241 12.434 12.456  5.958 2234123.227 28433821.582   \n",
       "2014-12-31 13.492 13.719 13.229 13.464 13.479  5.353 2686450.437 36396421.270   \n",
       "2015-12-31 19.631 20.132 19.013 19.524 19.965  6.649 3739818.934 76198000.599   \n",
       "2016-12-31 16.207 16.575 15.790 16.139 21.057  3.076 2453864.820 54962953.932   \n",
       "2017-12-31 11.521 11.742 11.303 11.534 19.664  0.410 1168955.758 23252325.567   \n",
       "2018-12-31 12.523 12.784 12.232 12.477 16.566  0.307 1035280.300 17300824.970   \n",
       "2019-12-31 16.516 16.764 16.227 16.498 16.503  0.483 2068814.947 35446422.111   \n",
       "2020-12-31  8.756  8.935  8.574  8.753  8.763  0.687 4733306.291 40638944.930   \n",
       "\n",
       "                      总市值           流通市值  \n",
       "日期                                        \n",
       "2011-12-31 2494419354.839  502804980.645  \n",
       "2012-12-31 1911641975.309  477910493.827  \n",
       "2013-12-31 1869838235.294  467459558.824  \n",
       "2014-12-31 2638726530.612  659681632.653  \n",
       "2015-12-31 4502369877.049 1125592469.262  \n",
       "2016-12-31 4741939549.180 2274862961.066  \n",
       "2017-12-31 5398211065.574 5398211065.574  \n",
       "2018-12-31 5643543007.407 5592958333.333  \n",
       "2019-12-31 7421647929.032 7219863918.415  \n",
       "2020-12-31 5915096163.369 5788482477.131  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#按照年来统计\n",
    "data_year = data.resample('A-DEC').mean()\n",
    "data_year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[(0, 1, 0),\n",
       " (0, 1, 1),\n",
       " (0, 1, 2),\n",
       " (0, 1, 3),\n",
       " (0, 1, 4),\n",
       " (1, 1, 0),\n",
       " (1, 1, 1),\n",
       " (1, 1, 2),\n",
       " (1, 1, 3),\n",
       " (1, 1, 4),\n",
       " (2, 1, 0),\n",
       " (2, 1, 1),\n",
       " (2, 1, 2),\n",
       " (2, 1, 3),\n",
       " (2, 1, 4),\n",
       " (3, 1, 0),\n",
       " (3, 1, 1),\n",
       " (3, 1, 2),\n",
       " (3, 1, 3),\n",
       " (3, 1, 4),\n",
       " (4, 1, 0),\n",
       " (4, 1, 1),\n",
       " (4, 1, 2),\n",
       " (4, 1, 3),\n",
       " (4, 1, 4)]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 设置参数范围\n",
    "ps = range(0, 5)\n",
    "qs = range(0, 5)\n",
    "ds = range(1, 2)\n",
    "#创建一个迭代器，生成表示ps, ds, qs中的项目的笛卡尔积的元组\n",
    "parameters = product(ps, ds, qs)\n",
    "parameters_list = list(parameters)\n",
    "parameters_list"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "\n",
    "# SARIMAX参数说明\n",
    " '''\n",
    "    趋势参数：（与ARIMA模型相同）\n",
    "    p：趋势自回归阶数。\n",
    "    d：趋势差分阶数。\n",
    "    q：趋势移动平均阶数。\n",
    "    \n",
    "    季节性参数：\n",
    "    P：季节性自回归阶数。\n",
    "    D：季节性差分阶数。\n",
    "    Q：季节性移动平均阶数。\n",
    "    m：单个季节期间的时间步数。\n",
    " '''"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ARIMA:(0, 1, 0) AIC:4025.8552230724454\n",
      "ARIMA:(0, 1, 1) AIC:3977.8805130174333\n",
      "ARIMA:(0, 1, 2) AIC:3936.107825643909\n",
      "ARIMA:(0, 1, 3) AIC:3895.671207656556\n",
      "ARIMA:(0, 1, 4) AIC:3860.9152145060607\n",
      "ARIMA:(1, 1, 0) AIC:4020.850792512817\n",
      "ARIMA:(1, 1, 1) AIC:3979.880822278879\n",
      "ARIMA:(1, 1, 2) AIC:3938.1213412384195\n",
      "ARIMA:(1, 1, 3) AIC:3897.3515255092434\n",
      "ARIMA:(1, 1, 4) AIC:3862.0005346969815\n",
      "ARIMA:(2, 1, 0) AIC:3980.3134203647337\n",
      "ARIMA:(2, 1, 1) AIC:3982.01735406477\n",
      "ARIMA:(2, 1, 2) AIC:3939.460670995231\n",
      "ARIMA:(2, 1, 3) AIC:3898.8666309287332\n",
      "ARIMA:(2, 1, 4) AIC:3863.652424746134\n",
      "ARIMA:(3, 1, 0) AIC:3938.713659674512\n",
      "ARIMA:(3, 1, 1) AIC:3937.994022608336\n",
      "ARIMA:(3, 1, 2) AIC:3936.759456672206\n",
      "ARIMA:(3, 1, 3) AIC:3898.5808961169496\n",
      "ARIMA:(3, 1, 4) AIC:3864.8657408380027\n",
      "ARIMA:(4, 1, 0) AIC:3898.944988998787\n",
      "ARIMA:(4, 1, 1) AIC:3898.8323898103504\n",
      "ARIMA:(4, 1, 2) AIC:3899.9052412795377\n",
      "ARIMA:(4, 1, 3) AIC:3900.5519191072462\n",
      "ARIMA:(4, 1, 4) AIC:3915.6891862695666\n",
      "最优模型:                                 SARIMAX Results                                \n",
      "==============================================================================\n",
      "Dep. Variable:                   成交金额   No. Observations:                  110\n",
      "Model:               SARIMAX(0, 1, 4)   Log Likelihood               -1925.458\n",
      "Date:                Tue, 20 Oct 2020   AIC                           3860.915\n",
      "Time:                        23:29:46   BIC                           3874.137\n",
      "Sample:                    09-30-2011   HQIC                          3866.272\n",
      "                         - 10-31-2020                                         \n",
      "Covariance Type:                  opg                                         \n",
      "==============================================================================\n",
      "                 coef    std err          z      P>|z|      [0.025      0.975]\n",
      "------------------------------------------------------------------------------\n",
      "ma.L1         -0.4560      0.078     -5.846      0.000      -0.609      -0.303\n",
      "ma.L2         -0.0410      0.076     -0.536      0.592      -0.191       0.109\n",
      "ma.L3         -0.1216      0.109     -1.119      0.263      -0.335       0.091\n",
      "ma.L4          0.0174      0.110      0.158      0.875      -0.199       0.234\n",
      "sigma2      7.297e+14   8.44e-17   8.65e+30      0.000     7.3e+14     7.3e+14\n",
      "===================================================================================\n",
      "Ljung-Box (Q):                       38.39   Jarque-Bera (JB):               273.35\n",
      "Prob(Q):                              0.54   Prob(JB):                         0.00\n",
      "Heteroskedasticity (H):               1.47   Skew:                             1.75\n",
      "Prob(H) (two-sided):                  0.26   Kurtosis:                        10.13\n",
      "===================================================================================\n",
      "\n",
      "Warnings:\n",
      "[1] Covariance matrix calculated using the outer product of gradients (complex-step).\n",
      "[2] Covariance matrix is singular or near-singular, with condition number 3.29e+46. Standard errors may be unstable.\n"
     ]
    }
   ],
   "source": [
    "#我们现在可以使用上面定义的参数三元组来自动化不同组合对ARIMA模型进行培训和评估的过程。 \n",
    "#在统计和机器学习中，这个过程被称为模型选择的网格搜索（或超参数优化）\n",
    "\n",
    "#在评估和比较配备不同参数的统计模型时，可以根据数据的适合性或准确预测未来数据点的能力，对每个参数进行排序。 \n",
    "#我们将使用AIC （Akaike信息标准）值，该值通过使用statsmodels安装的ARIMA型号方便地返回。 \n",
    "#AIC衡量模型如何适应数据，同时考虑到模型的整体复杂性。 \n",
    "#在使用大量功能的情况下，适合数据的模型将被赋予比使用较少特征以获得相同的适合度的模型更大的AIC得分。 因此，我们有兴趣找到产生最低AIC值的模型。\n",
    "\n",
    "#下面的代码块通过参数的组合来迭代，并使用SARIMAX函数来适应相应的季节性ARIMA模型。 这里， order参数指定(p, d, q)参数，\n",
    "\n",
    "# 寻找最优ARMA模型参数，即best_aic最小\n",
    "results = []\n",
    "best_aic = float(\"inf\") # 正无穷\n",
    "for param in parameters_list:\n",
    "    try:\n",
    "        #model = ARIMA(df_month.Price,order=(param[0], param[1], param[2])).fit()\n",
    "        model = sm.tsa.statespace.SARIMAX(data_month['成交金额'],\n",
    "                                order=(param[0], param[1], param[2]),\n",
    "                                #seasonal_order=(4, 1, 2, 12),\n",
    "                                enforce_stationarity=False,\n",
    "                                enforce_invertibility=False).fit()\n",
    "\n",
    "    except ValueError:\n",
    "        print('参数错误:', param)\n",
    "        continue\n",
    "    aic = model.aic\n",
    "    #打印p,q,d和aic\n",
    "    print('ARIMA:{} AIC:{}'.format(param,  aic))\n",
    "    if aic < best_aic:\n",
    "        best_model = model\n",
    "        best_aic = aic\n",
    "        best_param = param\n",
    "    results.append([param, model.aic])\n",
    "\n",
    "# 输出最优模型\n",
    "print('最优模型: ', best_model.summary())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "从上面的输出可以看出最好的参数是：  \n",
    "Model:               SARIMAX(0, 1, 4)  \n",
    "AIC                 3860.915  \n",
    "\n",
    "p=0,q=1,d=4取这些值，模型效果最好，AIC为3860.915"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "date_list= [Timestamp('2020-11-30 00:00:00', freq='M'), Timestamp('2020-12-31 00:00:00', freq='M'), Timestamp('2021-01-31 00:00:00', freq='M')]\n"
     ]
    }
   ],
   "source": [
    "# 设置future_month，需要预测的时间date_list\n",
    "data_month2 = data_month[['成交金额']]\n",
    "future_month = 3\n",
    "last_month = pd.to_datetime(data_month2.index[len(data_month2)-1])\n",
    "date_list = []\n",
    "for i in range(future_month):\n",
    "    # 计算下个月有多少天\n",
    "    year = last_month.year\n",
    "    month = last_month.month\n",
    "    if month == 12:\n",
    "        month = 1\n",
    "        year = year+1\n",
    "    else:\n",
    "        month = month + 1\n",
    "    next_month_days = calendar.monthrange(year, month)[1]\n",
    "    #print(next_month_days)\n",
    "    last_month = last_month + timedelta(days=next_month_days)\n",
    "    date_list.append(last_month)\n",
    "print('date_list=', date_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>收盘价</th>\n",
       "      <th>最高价</th>\n",
       "      <th>最低价</th>\n",
       "      <th>开盘价</th>\n",
       "      <th>前收盘</th>\n",
       "      <th>换手率</th>\n",
       "      <th>成交量</th>\n",
       "      <th>成交金额</th>\n",
       "      <th>总市值</th>\n",
       "      <th>流通市值</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-09-30</th>\n",
       "      <td>23.385</td>\n",
       "      <td>24.475</td>\n",
       "      <td>22.465</td>\n",
       "      <td>23.540</td>\n",
       "      <td>24.040</td>\n",
       "      <td>42.130</td>\n",
       "      <td>8438575.500</td>\n",
       "      <td>201086176.410</td>\n",
       "      <td>2338500000.000</td>\n",
       "      <td>468401550.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-31</th>\n",
       "      <td>25.367</td>\n",
       "      <td>26.159</td>\n",
       "      <td>24.402</td>\n",
       "      <td>24.992</td>\n",
       "      <td>25.115</td>\n",
       "      <td>27.140</td>\n",
       "      <td>5436163.312</td>\n",
       "      <td>138331914.625</td>\n",
       "      <td>2536750000.000</td>\n",
       "      <td>508111025.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-11-30</th>\n",
       "      <td>26.828</td>\n",
       "      <td>27.327</td>\n",
       "      <td>26.182</td>\n",
       "      <td>26.671</td>\n",
       "      <td>26.780</td>\n",
       "      <td>15.615</td>\n",
       "      <td>3127619.045</td>\n",
       "      <td>84215481.706</td>\n",
       "      <td>2682772727.273</td>\n",
       "      <td>537359377.273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>22.895</td>\n",
       "      <td>23.502</td>\n",
       "      <td>22.569</td>\n",
       "      <td>23.111</td>\n",
       "      <td>23.248</td>\n",
       "      <td>8.104</td>\n",
       "      <td>1643899.273</td>\n",
       "      <td>39840843.355</td>\n",
       "      <td>2289454545.455</td>\n",
       "      <td>467519227.273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-31</th>\n",
       "      <td>20.243</td>\n",
       "      <td>20.699</td>\n",
       "      <td>19.757</td>\n",
       "      <td>20.177</td>\n",
       "      <td>20.199</td>\n",
       "      <td>4.495</td>\n",
       "      <td>1123700.600</td>\n",
       "      <td>22875662.247</td>\n",
       "      <td>2024333333.333</td>\n",
       "      <td>506083333.333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-30</th>\n",
       "      <td>6.739</td>\n",
       "      <td>6.874</td>\n",
       "      <td>6.641</td>\n",
       "      <td>6.767</td>\n",
       "      <td>6.769</td>\n",
       "      <td>0.421</td>\n",
       "      <td>3403999.182</td>\n",
       "      <td>23218949.166</td>\n",
       "      <td>5570956211.883</td>\n",
       "      <td>5453726699.667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-31</th>\n",
       "      <td>6.955</td>\n",
       "      <td>7.093</td>\n",
       "      <td>6.805</td>\n",
       "      <td>6.937</td>\n",
       "      <td>6.867</td>\n",
       "      <td>0.530</td>\n",
       "      <td>4291013.333</td>\n",
       "      <td>29949636.543</td>\n",
       "      <td>5749440239.985</td>\n",
       "      <td>5628454892.190</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-30</th>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-31</th>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>113 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "              收盘价    最高价    最低价    开盘价    前收盘    换手率         成交量  \\\n",
       "2011-09-30 23.385 24.475 22.465 23.540 24.040 42.130 8438575.500   \n",
       "2011-10-31 25.367 26.159 24.402 24.992 25.115 27.140 5436163.312   \n",
       "2011-11-30 26.828 27.327 26.182 26.671 26.780 15.615 3127619.045   \n",
       "2011-12-31 22.895 23.502 22.569 23.111 23.248  8.104 1643899.273   \n",
       "2012-01-31 20.243 20.699 19.757 20.177 20.199  4.495 1123700.600   \n",
       "...           ...    ...    ...    ...    ...    ...         ...   \n",
       "2020-09-30  6.739  6.874  6.641  6.767  6.769  0.421 3403999.182   \n",
       "2020-10-31  6.955  7.093  6.805  6.937  6.867  0.530 4291013.333   \n",
       "2020-11-30    nan    nan    nan    nan    nan    nan         nan   \n",
       "2020-12-31    nan    nan    nan    nan    nan    nan         nan   \n",
       "2021-01-31    nan    nan    nan    nan    nan    nan         nan   \n",
       "\n",
       "                    成交金额            总市值           流通市值  \n",
       "2011-09-30 201086176.410 2338500000.000  468401550.000  \n",
       "2011-10-31 138331914.625 2536750000.000  508111025.000  \n",
       "2011-11-30  84215481.706 2682772727.273  537359377.273  \n",
       "2011-12-31  39840843.355 2289454545.455  467519227.273  \n",
       "2012-01-31  22875662.247 2024333333.333  506083333.333  \n",
       "...                  ...            ...            ...  \n",
       "2020-09-30  23218949.166 5570956211.883 5453726699.667  \n",
       "2020-10-31  29949636.543 5749440239.985 5628454892.190  \n",
       "2020-11-30           nan            nan            nan  \n",
       "2020-12-31           nan            nan            nan  \n",
       "2021-01-31           nan            nan            nan  \n",
       "\n",
       "[113 rows x 10 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# 添加未来要预测的3个月\n",
    "future = pd.DataFrame(index=date_list, columns= data_month.columns)\n",
    "data_month = pd.concat([data_month, future])\n",
    "data_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>成交金额</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-09-30</th>\n",
       "      <td>201086176.410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-31</th>\n",
       "      <td>138331914.625</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-11-30</th>\n",
       "      <td>84215481.706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>39840843.355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-31</th>\n",
       "      <td>22875662.247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-30</th>\n",
       "      <td>23218949.166</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-31</th>\n",
       "      <td>29949636.543</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-30</th>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-31</th>\n",
       "      <td>nan</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>113 rows × 1 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    成交金额\n",
       "2011-09-30 201086176.410\n",
       "2011-10-31 138331914.625\n",
       "2011-11-30  84215481.706\n",
       "2011-12-31  39840843.355\n",
       "2012-01-31  22875662.247\n",
       "...                  ...\n",
       "2020-09-30  23218949.166\n",
       "2020-10-31  29949636.543\n",
       "2020-11-30           nan\n",
       "2020-12-31           nan\n",
       "2021-01-31           nan\n",
       "\n",
       "[113 rows x 1 columns]"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_month.drop(columns=['收盘价','最高价','最低价','开盘价','前收盘','换手率','成交量','总市值','流通市值'], inplace=True)\n",
    "data_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>成交金额</th>\n",
       "      <th>预测成交金额</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2011-09-30</th>\n",
       "      <td>201086176.410</td>\n",
       "      <td>0.000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-10-31</th>\n",
       "      <td>138331914.625</td>\n",
       "      <td>201086176.410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-11-30</th>\n",
       "      <td>84215481.706</td>\n",
       "      <td>166948347.170</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2011-12-31</th>\n",
       "      <td>39840843.355</td>\n",
       "      <td>124512151.466</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2012-01-31</th>\n",
       "      <td>22875662.247</td>\n",
       "      <td>89471518.576</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-09-30</th>\n",
       "      <td>23218949.166</td>\n",
       "      <td>55737856.350</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-10-31</th>\n",
       "      <td>29949636.543</td>\n",
       "      <td>33390640.794</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-11-30</th>\n",
       "      <td>nan</td>\n",
       "      <td>30852454.812</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-31</th>\n",
       "      <td>nan</td>\n",
       "      <td>35305337.236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2021-01-31</th>\n",
       "      <td>nan</td>\n",
       "      <td>35158278.891</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>113 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                    成交金额        预测成交金额\n",
       "2011-09-30 201086176.410         0.000\n",
       "2011-10-31 138331914.625 201086176.410\n",
       "2011-11-30  84215481.706 166948347.170\n",
       "2011-12-31  39840843.355 124512151.466\n",
       "2012-01-31  22875662.247  89471518.576\n",
       "...                  ...           ...\n",
       "2020-09-30  23218949.166  55737856.350\n",
       "2020-10-31  29949636.543  33390640.794\n",
       "2020-11-30           nan  30852454.812\n",
       "2020-12-31           nan  35305337.236\n",
       "2021-01-31           nan  35158278.891\n",
       "\n",
       "[113 rows x 2 columns]"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# get_prediction得到的是区间，使用predicted_mean\n",
    "data_month['预测成交金额'] = best_model.get_prediction(start=pd.to_datetime('2011-09-30'), end=pd.to_datetime('2021-01-31')).predicted_mean\n",
    "data_month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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hp59+OsuXL+fwww9nxowZXHHFFQBMnjyZa665ht/+9rdMnDiRo48+mhtvvJEzzzwzo59tVwzLJEmSJEmSJEmSBpAYI5s3b+aZZ57hpz/9Kd/+9rc7HDd//nweeOAB7rnnHoYMGcL73/9+7r33XkIIFBUlEVEIgQULFnDrrbdyxBFH8M53vpM1a9Zw8803c+ONN7bP9bOf/YyZM2fy6quv0traSkFBAalUii9/+cu88sorTJw4kcMOO4zq6mpKSkoAuPrqqzn++OPbW0S2eeyxxzjnnHN44IEHiDEyb948Vq9ezeTJk1m2bFl7QNdXDMskSZIkSZIkSZJ6qbsKsGxZs2YN5513HsOGDQPg1FNPZe3atcydOxeA2tparrrqKgBOPPFEfvSjH5FKpTjmmGMA+M53vsPw4cO54IIL2sdfccUVzJw5kwULFnDCCSdwxRVXUFxczNSpU9vXvfDCCwG49NJLue+++6ioqGDdunVceeWVb9vftm3bOOOMMygrK+Mvf/kLv/71rxkxYgS1tbUsXryYkpISDj74YBYtWsSUKVOYM2cO8+fPZ8KECWzbto2RI0eyYcOG7H6Iu8laWBZCuB2YDrwOfDzG2Lzb/VLgV8BBwGrgXGDI7tdiW9PMTnR9V5IkSZIkSZIkKX+84x3v4L/+67/a33/lK19h1qxZnHDCCZxwwgnt11tbW/noRz/KRz7yEe69916+8Y1vcOONN/LpT3+a2bNnc95551FcXMy6des49dRTefHFFykpKeGYY45hxYoV3HvvvR2u/7WvfY0PfvCDDBs2jEWLFu1xf+zYsZx99tlMnz6dZcuWcfzxx1NdXc3UqVPbK85SqRSrVq3iuOOOY+nSpXzmM5/hueeeY9WqVcycOZOtW7dm+FPrWkE2Jg0hHA8UxRiPBSqBUzoYNh/YGGM8ChgBnNzJtS69tKVu7zZ50klwzjl796wkSZIkSZIkSVI/iTGyYsUKPv7xjxNj5HOf+xy33norc+fO5U9/+lP7mIcffpgRI0bwiU98gsLCQpqbmxkzZgwf+MAHWL58Oa2trSxZsoRDDz2UG264gXPOOYeLL76Yk08+mVtuuYUHH3yQ1atX09LSwtq1a7nrrru4+OKLOeSQQ6ioqOCSSy7hV7/6FU888UT73pqbm5k1axabNm1qv/bQQw8xa9YsmpqaADj88MOZPn06jz76KM8++ywlJSXMmzePZ555htdee42tW7fS3NxMX8lWZdlrwA3pnzsL5E4C7k7/vBiYA0zq4Npvu1qosbl173a4ZEny+rOf7d3zkiRJkiRJkiRJ/eDcc88F4F//9V/5m7/5GwB++tOfsnjxYq6++mr+4z/+gxgj5eXlnHvuubS0tDBnzhwOO+wwIGnFGELg3nvv5ZhjjmHSpEncddddzJ49mw9/+MPccsst/Nu//Ruf/OQnWbZsGa+//joXXXQRJ510Etdeey3Tpk0D4Omnn2bhwoWsWLGC4447DoCLL76YDRs2EEIAYPny5RQVFXH22Wdz5JFHct111wGwc+dO7r//fu677z6WLVvG1Vdfzc9//nMOOugg/vEf/5E1a9a07zfbQjddDvdt8hD+FrgE+EAHbRgfBq6LMT4SQvgsUAVM3v1ajPHCrtYoHX9IrH95TfuH3mOjR8OZZ8IPftC75yRJkiRJkiRJ0qD0/PPPc+ihh/b3NjKqsbGxvT3iq6++yrhx49rvbdy4kQkTJvT5PjrT0ecfQlgZY5yxL2tnpQ0jQAjhI8AXgNN3D8rS3gCGp38enn7f0bWO5r4ghFAdQqiOEV5/c2fvN1hXBxUVvX9OkiRJkiRJkiQpT+waUO0alAF9FpTtvo++lq0zy8YBlwMfjjG+2cmwR3nrLLOTgCWdXNtDjPGWGOOMtqRw/Ru1vdtgayvU18OCBXD++b17VpIkSZIkSZIkSXkjW5Vlfw8cADwcQlgeQviHEMKC3cb8B3BgCGE1sIUkKOvoWrc2bKnr3e5CgHXr4P3vhwcfhCy2opQkSZIkSZIkSVLuKsrGpDHGfwf+vZsxO4EP73a5o2vd2lDTy8qyEODgg+GMM+Cii2DtWnjHO3q7rCRJkiRJkiRJkga4rJ1Z1ldKCgvYUNPLyrItW+Cb34QDDkjeL+mw26MkSZIkSZIkSdKA19TU1O2YdevWdXl/5cqVbNy4sX2+mO7a19raSktLy75vsh8N/LCsqICXetuG8eWX4atfhcZGGD8eFi/OzuYkSZIkSZIkSZKyaO7cuTQ0NHD55ZdTX1+/x/0bbriB6667rss51qxZw7HHHssPfvCDTscsXLiQRx9NTs/6/ve/z2mnncb48eP52Mc+xuIBnrNkpQ1jXxpSVMD6N3rZhrE2Pb6iAr7wBRg6NPMbkyRJkiRJkiRJyrJUKgXAIYccwrp16zj88MOZOXMmlZWVADQ2NlJSUsLjjz9OjJH6+noef/zx9ue3b9/O/PnzWbhwIbfddhvXX389l1xyCYWFhQD84he/4Morr2T//fdn6dKlXH755WzcuJHTTjuN733ve3z3u9/t+186w/KisizV0My2usaeP7RrWPblL8PnPpedzUmSJEmSJEmSJGXQrbfeyrve9S7mzp3L3LlzWbduHR/60Ie4++67+fznP89rr73GihUrWLRoEbNmzeLBBx/kN7/5DfPmzWPhwoVvC8rWrl3LKaecwjXXXMOxxx7LTTfdRE1NDVVVVdx8883U1NQwfvx4vvjFL1JeXs7SpUu54447+MMf/sDtt9/Oli1b+OUvf9mPn0ZmDPjKspKiAhqB9TV1HF1e0rOHduxIXisqktft22HrVpg8ORtblCRJkiRJkiRJ+Wj27D2vnXkmXHwx1NXBhz605/1Pfzr598Yb8MlPvv3e0qXdLllQUMCll17KZz/7WQDOP/98LrvsMtavX8/48eMZN24cdXV1nHfeeUydOpXS0lIAtm7dypw5c7jzzjuZOHEizz33HPPmzePEE0/k61//Ol/60pcoKyujsLCQ008/neXLl3P44YczY8YMrrjiCgAmT57MNddcw29/+1smTpzI0UcfzY033siZZ57Z888sBw38sKywkEZgQ00tRx+0X88e2rWyDODd74Yjj4R77snKHiVJkiRJkiRJkjIhhMCCBQu49dZbOeKII3jnO9/JmjVruPnmm7nxxhsB+NnPfsbMmTN59dVXaW1tpaCggFQqxZe//GVeeeUVJk6cyGGHHUZ1dTUlJUkh0tVXX83xxx/P7N0CwMcee4xzzjmHBx54gBgj8+bNY/Xq1UyePJlly5Yxbty4vv4IMm7Ah2VDigrYAWyoqev5Q5/8JLz//TBqVPL+hBPg/vuhtRUKBnxnSkmSJEmSJEmS1Be6qgQrL+/6/ujRPaok211tbS1XXHEFM2fOZMGCBZxwwglcccUVFBcXM3XqVAAuvPBCAC699FLuu+8+KioqWLduHVdeeeXb5tq2bRtnnHEGZWVl/OUvf+HXv/41I0aMoLa2lsWLF1NSUsLBBx/MokWLmDJlCnPmzGH+/PlMmDCBbdu2MXLkSDZs2NDr3yHXDPiwLAQYV1nau7CspAT23/+t93PmwG23werVcPTRmd+kJEmSJEmSJElSBqxbt45TTz2VF198kZKSEo455hhWrFjBvffeu8fYr33ta3zwgx9k2LBhLFq0aI/7Y8eO5eyzz2b69OksW7aM448/nurqaqZOndpecZZKpVi1ahXHHXccS5cu5TOf+QzPPfccq1atYubMmWzdujXrv3O25UUZ1cRR5Wyoqe35A48+Cv/2b0klGSRhGcCSJZnfnCRJkiRp0Hr9zQZijP29DUmSJOWJ1tZWlixZwqGHHsoNN9zAOeecw8UXX8zJJ5/MLbfcwoMPPsgzzzzD2rVrueuuu7j44os55JBDqKio4JJLLuFXv/oVTzzxRPt8zc3NzJo1i02bNrVfe+ihh5g1axZNTU0AHH744UyfPp1HH32UZ599lpKSEubNm8czzzzDa6+9xtatW2lubu7zzyKT8iIsmzyqnA1belFZ9uijcO21b7VcnDABpk0zLJMkSZIkZcym7fUcd+1ilq19o7+3IkmSpDxx//33c8wxxzBp0iTuuusuPv/5zzNlyhTuvvtupk+fzic/+Ul27NjBRRddxJo1a7j22mu58847WbRoERdeeCGrV6/mrrvuap/v4osv5tJLL+UnP/kJy5cv55vf/CZFRUWcffbZ/Mu//Ev7uJ07d3L//fdz+eWXs2zZMubPn8+Pf/xjLrroIgoKClizZk1/fBwZEwb6X7jNmDEjnnfdf3Ldw3/muW+cSnlJDzpLXnIJ3H47bNv21rXFi2HcODjssOxtVpIkSZI0aKzcsJVP3LSCqz/2LuYfO6m/tyNJkqQMeP755zn00EP7dQ+NjY3tLRJfffVVxo0b135v48aNTJgwoU/30Jc6+vxDCCtjjDP2Zd4Bf2YZwKRR5QBsqKnj0AMqu3+gthYqKt5+7aSTsrAzSZIkSdJglWpI2tZsr2/q551IkiQpn+waUu0alAF9EpTtvod8kBdtGCeNTIKvDTU9bMXYUVgWI9xxBzz8cIZ3J0mSJEkajFLpkCxlWCZJkpRXBnrHvoEqm597XoRlE9sry2p79kBHYVkIcPXV8J3vZHh3kiRJkqTBKNWQHHK+rc6wTJIkKV+UlpZSU1NjYNbHYozU1NRQWlqalfnzog3j8LJiRpQXs2FLDyvL7r0Xdu7c8/qcOclZZk1NUFyc2U1KkiRJkgaVtooy2zBKkiTljwkTJrBx40Y2b97c31sZdEpLS7PWZjIvwjKASaMqel5ZVlgI5eV7Xp8zB37wA6iuhuOOy+wGJUmSJEmDimGZJElS/ikuLmbKlCn9vQ1lWF60YQSYNKq852eWXXVVUkG2u9mzk9clSzK2L0mSJEnS4JRqMCyTJEmSBoI8CssqeGVbPY3Nrd0Pvu02eOSRPa+PHg1HHAHPP5/5DUqSJEmSBpVUfXJmmWGZJEmSlNvypw3jyHJaI2zcWsfBY4Z2Pbi2FioqOr63fDlUVmZ+g5IkSZKkQaWtsixlWCZJkiTltDyqLEvOINuwpQetGHfs6DwsMyiTJEmSJGVAW0j25s5mWlpjP+9GkiRJUmfyKCxLwq8Nb9R2PbC1FerqOg/LWlvhrLPghhsyvENJkiRJ0mCSamh+62eryyRJkqSclTdh2eihJZSXFHZfWdbQAKWlMLSTVo0FBfA//wP33pv5TUqSJEmSBo1UfRMVJYUAbDMskyRJknJW3pxZFkJg0qgKNtR0E5aVl0N9PcQuWmDMmQM33piMKyvL7EYlSZIkSXkvxsj2+iamjR3K/7z6JtsNyyRJkqSclTeVZQCTRpazoaabNoxtQuj83kknQWMjPPFEZjYmSZIkSRpU6ptaaG6NTBiRnK9tWCZJkiTlrvwKy0aX89ct9V0fnPzSS3DOObByZedjZs2CwkJYsiTzm5QkSZIk5b1UfXJe2UEjk24lhmWSJElS7sqvsGxkBY0trbyaauh80KZN8POfw6uvdj6mshLOOgvGjs38JiVJkiRJeS/VkIRjB1lZJkmSJOW8vDmzDGDyqORLyIaaWg7cr5OzxmrTbRqHDu16sp/+NIM7kyRJkiQNJql0ODZxZPnb3kuSJEnKPXlVWTaxPSyr63xQW1hWUdH9hM3NkEplYGeSJEmSpMGkrbJszLAhDCkqsLJMkiRJymF5FZYdMLyM4sKQmbCssRH23x+uuSZzG5QkSZIkDQptZ5ZVlhWzX3kx2+sMyyRJkqRclVdhWWFB4KCR5Wyoqe18UAgwenT3bRhLSuDQQ2HJksxuUpIkSZKU99oqySpLixheVmxlmSRJkpTD8iosA5g0srzryrK/+zvYvBkOOqj7yebMgZUrbcUoSZIkSeqVtjPKhpUWM7ysmG31jf28I0mSJEmdyb+wbFQFG2pqiTHu+2Rz5kBLCyxbtu9zSZIkSZIGjVRDE2XFhZQUFaQry5r7e0uSJEmSOpGHYVk5tY0t1NR28ld7t98OZ5zRs8mOOy5px2grRkmSJElSL6Tqm6ksKwKSc8tStmGUJEmSclZRf28g0yaPqgBgQ00to4cO2XPAqlXw8MM9m6ysDL7/fTjqqAzuUK3cJecAACAASURBVJIkSZKU71INTVSWFgN4ZpkkSZKU4/KusmziqHKAzs8tq62FioqeT/jZz0JVVQZ2JkmSJEkaLFINTQwveyss27GzmeaW1n7elSRJkqSOZDUsCyEUhxAWdnF/dghhefrfX0MIfx9CqAohbNzl+vTerDlhRBkFIYNhWXMz/O538Kc/9WYbkiRJkqRBLGnD+FZYBpBq8NwySZIkKRdlLSwLIZQBK4GTOxsTY1waYzw+xng8sBr4AzACuKnteozxz71Zd0hRIQcML2NDTW3HA2prYejQnk/Y0gIf/SjccktvtiFJkiRJGsS21zdRWZqcfNAWltmKUZIkScpNWQvLYoz1McYjgY3djQ0hlAPTYoyrScKyT4QQngoh3B1CCL1de9KocjZs6aSybPRomDq155MNGQIzZ8KSJb3dhiRJkiRpkEo1NLVXlu1XblgmSZIk5bJcObPsZODR9M8vAFfEGN8DHACc2NvJJo2q6LwN4623wt13927COXPgj3+EzZt7uxVJkiRJ0iATYyRV30Rl6dvbMBqWSZIkSbkpV8Ky04FF6Z/XA4/s8vPY3QeHEC4IIVSHEKo3dxBgTRpVzpbaRlINGfoiMmdO8rp0aWbmkyRJkiTlrdrGFlojVJa9vQ3jtrrG/tyWJEmSpE70e1iWbrM4G1icvvRPwLwQQgHwLuDZ3Z+JMd4SY5wRY5wxZsyYPeacPKocgJc6qi77u7+Df//33m1yxozknLPly3v3nCRJkiRp0EmlK8jaKsva2jGmrCyTJEmSclKfhWUhhCkhhAUd3KoCnosxNqTf3wicBzwJ3BtjfK63a00cWQHQcSvGxx6Ddet6N2FxMfz3f8P11/d2K5IkSZKkQaaty0lbRZltGCVJkqTcVpTtBWKM09KvLwL/3MH9p4CP7PJ+E0ml2V6blK4sW19Tu+fN2lqoqOj9pIccsi9bkiRJkiQNEqn6ZuCtirIhRYWUFhcYlkmSJEk5qt/bMGZDxZAiRg8dsmcbxhj3PixLpeB//S/4zW8ys0lJkiRJUl7avlsbRkiqywzLJEmSpNyU9cqy/jJ5VDkbtuxWWdbQkARmexOWVVTAz36WzPHBD2Zmk5IkSZKkvNN+ZlnZW1+5DcskSZKk3JWXlWUAE0eV73lmWVMTVFXBxIm9n7CwEE44AZYsycwGJUmSJEl5qe3Msl0ry/YrKzEskyRJknJU3oZlk0ZWsGl7Aw1NLW9drKyEp56Cs8/eu0nnzIF16+Cvf83MJiVJkiRJeaftzLJhpW9VllWWFbM9fV2SJElSbsnbsGzy6HIA/rqlrpuRvXDSScmr1WWSJEmSpE6kGpqoKCmkqPCtr9zDy4rb2zNKkiRJyi15G5ZNHJmEZW9rxfjHP8Ixx8CKFXs36RFHJP/q6zOwQ0mSJElSPkrVN1FZVvy2a8PLitlW19hPO5IkSZLUlaLuhwxMk0dVALC+pvati2+8AatWwc6dezdpQQGsXp2B3UmSJEmS8lWqoYnhHYRltY0tNLW0UlyYt3+3KkmSJA1Iefs/9P3KixlWWsRLu7ZhrE0HZxUV+zZ5jNDS0v04SZIkSdKgs72+icrS3cOy5G9VbcUoSZIk5Z68DctCCEweVfH2NoyZCMs2bYJJk+D22/dtg5IkSZKkvJSqb6ay7O2NXIaXJ+HZdsMySZIkKefkbVgGMHFUORt2bcOYibBs3LikjeNjj+3b5iRJkiRJeSnV0FFlmWGZJEmSlKvyOiybPKqcjVvraW5pTS6MGQMnngjDh+/9pCHAe94D1dWZ2aQkSZIkKa+k6puo7ODMMjAskyRJknJRXodlk0ZW0NwaeWVbQ3Lh9NNh6VIYMWLfJq6qguefhzff3Oc9SpIkSZLyR2tr5M2dzVSW7taGsawEMCyTJEmSclFeh2UTR5UDsGFLbTcje2nGDIgR/vCHzM4rSZIkSRrQdjQ2EyOdVpalDMskSZKknJPXYdnkUcnZZOtr6pILV10Ff/M3+z5xVRV87nMwcuS+zyVJkiRJyhttYVhnYdm2OsMySZIkKdcUdT9k4Bo7bAhDigp4qSZdWfbyy/DKK/s+8ZgxcOON+z6PJEmSJCmvtLVZrCx9e1hWUlRAWXGhbRglSZKkHJTXlWUFBYFJo8rfqizbsQMqKjIzeXNzcm6ZJEmSJElpqfpmACrL9vzb1OFlxYZlkiRJUg7K67AMYOLICl5qC8tqazMXlv3f/wuHHQZbt2ZmPkmSJEnSgJdq6LiyDAzLJEmSpFyV92HZ5FHlbNhSS4wxs2HZu9+dvK5cmZn5JEmSJEkDXtuZZcPLDMskSZKkgSLvw7JJo8ppaGrl9Td3wrHHwkknZWbitrCsujoz80mSJEmSBrxUQ7oNYweVZZWGZZIkSVJO2rOJep6ZNCqpJNtQU8f+3/hG5iYeMQKmToWnn87cnJIkSZKkAa2tsmxo6Z5ft/crL+a5VwzLJEmSpFwzKCrLANbX1GZ+8qoqK8skSZIkSe1SDU0MKy2isCDscc82jJIkSVJuyvuwbPx+ZRQWBF6qqYPDDoPLL8/c5F/4AvzwhxBj5uaUJEmSJA1Y2+ubOmzBCElYVtvYQlNLax/vSpIkSVJX8r4NY3FhARNGlCWVZS+/DE0Z/Cu+447L3FySJEmSpAEvVd9MZVnnYRkkgdrooUP6cluSJEmSupD3lWUAE0eW81JNLdTWQkVFZidfvBiWL8/snJIkSZKkASnV0ERlB+eVwdvDMkmSJEm5Y1CEZZNHVfDya9ugpSXzYdnnPw/f+lZm55QkSZIkDUip+qYeVZZJkiRJyh2DIiybNKqcljd3JG8yHZZVVcHTT3tumSRJkiSJNxuaOz2zrNKwTJIkScpJgyQsq6A1FLDljLPgXe/K7OQzZsCrr8Irr2R2XkmSJEnSgJNUlnXdhjFlWCZJkiTllEESlpWTKh3Ksn/5Frz//ZmdvKoqeX366czOK0mSJEkaUFpaI2/ubG4PxXZnG0ZJkiQpNw2KsGziyHKIkZdq6jI/+VFHQWEhVFdnfm5JkiRJ0oDxZkMSgnXWhrE9LKszLJMkSZJySce9IfJMaXEhH9yyhotP/Vt49BE48cTMTV5WBqtXw7RpmZtTkiRJkjTgpOqbgbfOJttdSVEB5SWFVpZJkiRJOWZQhGUAE4dECluaobQ085Mfdljm55QkSZIkDSip9sqyzr9qDy8rNiyTJEmScsygaMMIMGFIa/JDRUXmJ1+7Fi67DP7618zPLUmSJEkaEFLpEKyzyjJIwrJthmWSJElSThk0Ydn4oiQsqy8ekvnJUyn4zndgxYrMzy1JkiRJGhBS3ZxZBkmQZmWZJEmSlFsGTVg2trAFgI1NWfiVjzgCSkqgujrzc0uSJEmSBoS3zizrug1jyrBMkiRJyimDJiyrOOYobv+b03hxZ2HmJy8pgaOOMiyTJEmSpEGsrbJseDdtGK0skyRJknJLVsOyEEJxCGFhF/erQggbQwjL0/+mhxBKQwiLQgjPhBB+FkIImdjLqA+fwpUn/yPra1syMd2eqqpg5Upobc3O/JIkSZKknLa9vomCABUlXVeWGZZJkiRJuSVrYVkIoQxYCZzcxbARwE0xxuPT//4MzAc2xhiPSt/v6vkeGx5aGFMC62vqMjHdnmbMgPJy2LQpO/NLkiRJknJaqr6JYaXFFBR0/jef+5UVU9fYQlOLf2gpSZIk5YqshWUxxvoY45HAxi6GjQA+EUJ4KoRwd7qK7CTgd+n7i4E5GdnQZZfxu2/P56VshWXnnpsEZQcemJ35JUmSJEk5LdXQ3OV5ZQDDy5MWjVaXSZIkSbmjv88sewG4Isb4HuAA4ERgFLA9fT8FjMzISrW1tJSVs76mNiPT7aGwEDLTMVKSJEmSNACl6puoLO38vDJ46zwzwzJJkiQpd/R3WLYeeGSXn8cCbwDD09eGp9+/TQjhghBCdQihevPmzT1bqbaWWF7BK9vqaWzOUruLq66Cs87KztySJEmSpJyWaug+LKs0LJMkSZJyTn+HZf8EzAshFADvAp4FHgVOSd8/CViy+0MxxltijDNijDPGjBnTs5VqaykYWkFrhI1bs9SKccsWuO8+aG7OzvySJEmSpJyVqu9BG8a2sKzOsEySJEnKFX0WloUQpoQQFux2+UbgPOBJ4N4Y43PAfwAHhhBWA1tIwrN9V1tLUeVQADZsyVJYVlUF9fXw3HPZmV+SJEmSlLN6UllmG0ZJkiQp93T9J28ZEGOcln59Efjn3e5tAmbvdm0n8OGMb+Tcc6E5wgZ4qSZLYdmMGclrdTUceWR21pAkSZIk5aTt9U3tYVhnDMskSZKk3NPfbRj7zvnnM+yi8ykvKWR9TW121pg2DYYPh6efzs78kiRJkqSc1NTSSl1jS/uZZJ0xLJMkSZJyz+AJyzZtItTVMWlURfYqywoKYN48OOig7MwvSZIkScpJbzYkZ1dXlnbdwKW4sIDykkLDMkmSJCmHZL0NY8449FA491wmVf09a19/M3vr/PCH2ZtbkiRJkpSTUunwq7vKMoD9yooNyyRJkqQcMngqy2prYehQJo0u569b6mlpjdlbq7UVGhuzN78kSZIkKaekGtJhWWn3YVmlYZkkSZKUUwZHWNbYCM3NUFHBpJEVNLa08mqqITtrvf46jBgBP/5xduaXJEmSJOWcVH26DWMPKsuGG5ZJkiRJOWVwhGW1tclrRQWTR5UDsKGmNjtrjRkDJSXw9NPZmV+SJEmSlHPaK8vKuj/tYHhZMdvrDMskSZKkXDHowrKJ6bDspZq67KwVAsyYAdXV2ZlfkiRJkpRz2irFhltZJkmSJA04gyMsGzYMFiyAY4/lgOFlFBcG1mcrLAOoqoI//QnqsriGJEmSJClnpOp7fmaZYZkkSZKUWwZHWDZ8OHzxi3DEERQWBA4aWc5LW7LUhhGSyrKWFli1KntrSJIkSZJyRqqhicKCQHlJYbdjh5cVU9/UQmNzax/sTJIkSVJ3BkdYtmMHrFkDDQ0ATBpZzvo3slj19d73wte+Bvvvn701JEmSJEk5I1XfTGVpESGEbscOL0+qz6wukyRJknLD4AjLli+H6dPhD38AYNKoCl7aUkeMMTvr7b8/XH01TJ2anfklSZIkSTkl1dBEZQ/OK4O3zjUzLJMkSZJyw+AIy2rTLRcrKgCYNKqcHTubqaltzN6aO3bAU09lb35JkiRJUs5I1Tf16LwyMCyTJEmScs2gDMsmj0peN9RksRXjt78Nxx4LqVT21pAkSZIk5YRUQzOVZUU9GtsWlqUMyyRJkqScMCjDsomjygHYUFObvTWrqiBG+O//zt4akiRJkqScsL2+qT0E646VZZIkSVJuGZRh2YQRZRSELFeWzZiRvFZXZ28NSZIkSVJO2Js2jNvqsng0gCRJkqQeGxxh2cknw003QXlSUTakqJADhpdlt7Js9GiYPBmefjp7a0iSJEmSckKqoYnKHlaWVbZXljVnc0uSJEmSeqhnDdUHuqOOSv7t4uAxFazbnMWwDJLqMivLJEmSJCmv7WxuoaGplcrSnn3FLi4soKKk0DaMkiRJUo4YHGHZunVQVwdHHNF+adrYofzi6b/S2hopKAjZWfcrX4FG22pIkiRJUj57syGpEOtpZRkkrRgNyyRJkqTcMDjCsm98A5YuhQ0b2i9NGzuUusYWNqUaOHC/suys++53Z2deSZIkSVLOSKVDr56eWQZJsGZYJkmSJOWGwXFmWW0tVFS87dK0MUMBWPvam9ld++67YfHi7K4hSZIkSeo3qfbKsp7/Pep+5cXtIZskSZKk/jVow7JD9h8GwAuv78ju2l/9Knz3u9ldQ5IkSZLUb9oqxIbbhlGSJEkakAZtWDayooSRFSWs25zlsKyqCqqrs7uGJEmSJKnf7E0bRsMySZIkKXcM2rAMklaMWa8smzEDXn4ZNm3K7jqSJEmSpH6RakiHZVaWSZIkSQPS4AjLvvlN+PKX97g8dWwfhGVVVcmr1WWSJEmSlJdS9ekzy3pZWVbf1MLO5pZsbUuSJElSDw2OsOzkk+GEE/a4PG3sULbWNVGzY2f21j76aCgogFWrsreGJEmSJKnfpBqaKC4MlBb3/Ct22/lmVpdJkiRJ/a+ovzfQJx59FCZPhqlT33Z52tihALzw+g5GDR2SnbWHDoX162HChOzML0mSJEnqV6n6JipLiwkh9PiZtpaNqfomxg4rzdbWJEmSJPXA4Kgs+9CH4Ec/2uNye1i2OcutGA86CHrxpUmSJEmSNHCkGpp7dV4ZWFkmSZIk5ZL8D8uam6GxESoq9rg1fngp5SWF2T+37Nln4dOfho0bs7uOJEmSJKnPba9vMiyTJEmSBrD8D8tqa5PXDsKyEAJTxwzNflhWVwe33w5PPpnddSRJkiRJfS5pw9i7Uw72Ky8BDMskSZKkXDCowzJIWjFmPSw76igoLobq6uyuI0mSJEnqc6mGfagsqzMskyRJkvpb/odlO9JBWBdh2abtDezY2Zy9PQwZAkccYVgmSZIkSXkoVd9MZWnvwrK2SrTt9Vn8LipJkiSpR/I/LBs/Hh56CObM6fD2tLFDAViX7eqyqqokLIsxu+tIkiRJkvpUUlnWuzaMRYUFDB1SZBtGSZIkKQfkf1g2dCiceioceGCHt9vCsqy3YnzPe2DcOHjjjeyuI0mSJEnqMw1NLTQ2t/a6sgySVozb6huzsCtJkiRJvZH/Ydkrr8A998C2bR3enjSynOLCwAubsxyWfeYz8PzzMGZMdteRJEmSJPWZVENSGdbbM8vanklZWSZJkiT1u/wPy558Ej7xCdiwocPbRYUFTB5Vkf3KMkmSJElS3mkLu9rOIOuN4WW2YZQkSZJyQVbDshBCcQhhYTdjbg8h/D6E8OsQQlEIoSqEsDGEsDz9b/o+bWJHOgSrqOh0yLSxQ7N/ZhnAF78IH/949teRJEmSJPWJ7fXNQNJSsbeGlxUblkmSJEk5IGthWQihDFgJnNzFmOOBohjjsUAlcAowArgpxnh8+t+f92kjtbXJazdh2YYtdTQ2t+7TUt1qbITf/Q5aWrK7jiRJkiSpT+xLG8b9ykoMyyRJkqQckLWwLMZYH2M8EtjYxbDXgBt228sI4BMhhKdCCHeHEMI+baSHYVlLa2R9Te0+LdWtqqqk0u3P+5b/SZIkSZJyw1ttGPeisqzcyjJJkiQpF/TrmWUxxrUxxqdCCH8LtAK/BV4Arogxvgc4ADhxnxbpQVg2dcxQANa+luVWjDNmJK/V1dldR5IkSZLUJ1INSRvGyrK9ObOsmIamVnY2231EkiRJ6k/9GpYBhBA+AnwBOD3G2AysBx5J314PjO3gmQtCCNUhhOrNmzd3vcA//AMsWwaFhZ0OmTpmKCHAC9k+t2z6dBg2DH7/++yuI0mSJEnqE/tSWdbWutHqMkmSJKl/9WtYFkIYB1wOfDjG+Gb68j8B80IIBcC7gGd3fy7GeEuMcUaMccaYMWO6XuTAA+H447scUlZSyIQRZbywOcthWWEhXHABHHZYdteRJEmSJPWJVEMTJUUFlBZ3/geanRmeDstShmWSJElSv+p9n4i9FEKYAnwuxvjPu1z+e5JWiw+njyb7MXAjcCfweeDeGONz+7TwkiWwdSt8/ONdDps2Zmj2K8sAFizI/hqSJEmSpD6Rqm/aq6oyeCss21ZnWCZJkiT1p6yHZTHGaenXF4F/3u3evwP/3sFjszO2gZtugj/+sfuwbOxQVqyroaU1UlgQMrZ8h+rrk7PURo/O7jqSJEmSpKxK1TczfC/OK4O3wjLbMEqSJEn9q9/PLMu62lqoqOh22LSxQ9nZ3MrLW+uzu5+WFpgwAb7+9eyuI0mSJEnKulRDU/vZY73VZViWSsFZZ8GmTfuyPUmSJEk9YFiWNm3sUABe2PxmNyP3UWEhvPvd8Nhj2V1HkiRJkpR1mWjD2GFYds89cOed8NWv7sv2JEmSJPWAYVnatDHDAPrm3LITT0xaQ77xRvbXkiRJkiRlTaqhea8ryypLk/aNHYZlJ5yQvFpZJkmSJGWdYVna8PJiRg8d0jdh2ezZyeuyZdlfS5IkSZKUNUll2d6dWVZUWMCwIUUdh2UHHwxnngnPP7+PO5QkSZLUnfwPyxYtggULejR02tgK1vZFWFZVBWVlsHRp9teSJEmSJGVFjHGfziwDqCwr7jgsW70aDjoIampg8+Z92KUkSZKk7uzdn78NJAcf3OOh08YO5f5VrxBjJISQvT2VlMCtt8Lhh2dvDUmSJElSVtU3tdDUEvf6zDJIzi1LdRSWfeYzSZeUbdugeO/nlyRJktS9/K8s+8534Pe/79HQaWOG8mZDM5vf3JnlTQFnnQVHHZX9dSRJkiRJWZGqbwaSwGtvDS8rZltdB2HZiy/CYYcZlEmSJEl9IL/DspYWuOwyePjhHg0/ZP9hAH1zblljI9x3X9JaQ5IkSZI04KQakpCrsmzvm7YM76gNYyoFW7bAlClw001w7rn7sk1JkiRJ3cjvsKy2NnmtqOjR8GljhwLwwuY+CMtihE99Cm67LftrSZIkSZIyrq194r62YdwjLFu/PnmdMgVeeQXuuAN29MH3VEmSJGmQGhxh2dChPRo+dtgQhg0p6pvKsiFD4Ljj4LHHsr+WJEmSJCnj3qos24ewrLyDsOzFF5PXKVNg5syka8qTT+71GpKk/8/encfHVdf7H3+dyZ5M9q1NuqRJaOnesrTQAi1CiwIiiCxXReV61Z8LKioqbogbepWr4oLiVa8gi6Cyu7AWaIGWpXsLbdp0S9NmzySTTDKT+f7+OEnXrDNnliTv5+PBY5Iz53y/3zxo2nPm8/18PiIiIoMbH8GyYWaWWZZFRZE7OsEygGXLYMMGaG6OznwiIiIiIiLimL6eZVmp4ZVh7AoE8fl7jh5cvBgefBBOPdXeZGlZ8PLL4S5XREREREQGoGDZCSqjGSxbvtwux7h6dXTmExEREREREcc4klnWe63n2OyyCRPgqqvsKinZ2TBnDqxZE9ZaRURERERkYGM7WDZrFuzfDxddNOxLKovc1LV1HXnoiajFi+1yjK++Gvm5RERERERExFGtHc70LAOOL8X4zDPw2mtHv7/sMigpCXkOEREREREZXOi1IkaDpCSYNGlEl1QW2v3NquraOW1KbiRWdVRqKrz9NkyZEtl5RERERERExHEen5+0pASSE0Pfh9pvsOyLX4SpU+Gxx+zvv/e9cJYpIiIiIiJDGNuZZVu3wne+A3V1w76ksqg3WHY4SqUYp06168+LiIiIiIjIqOLpDJCVFt4e1JOCZcZAdTWUlZ18cnd3WHOJiIiIiEj/xnawbMMGuOUWaGkZ9iWT89JJTnRRVR+lYFldHXz0o7BqVXTmExEREREREUd4fP6wSjDC0WBZS29JR5qaoK0Npk07/sQlS+xnRxERERERcdzYDpZ5vfZrRsawL0lwWZQXZFBVF6VgWWYm/PnP8OST0ZlPREREREREHOHx+clKcyZYdiSzbM8e+/XEYNnEibBmTVhziYiIiIhI/xQs60dFkTt6wbK0NFi8GF54ITrziYiIiIiIiCM8nQGyUsMrw5h1YrCsutp+PbEM49Kl9nu1tWHNJyIiIiIiJ1OwrB+nFLnZ39yBz98TgUX1Y9kyeOMN8HiiM5+IiIiIiIiEzYnMsgSXRWZK4tFg2UUXwSuvwKmnHn/i0qX268svhzWfiIiIiIicbOwHy5KTIWlkDy+VRW6Mgd313ggt7ATLl0MwqJIaIiIiIiIio0hrZ/g9ywCy05Pw9AXLMjPhrLMgNfX4kxYutI/puVFERERExHEDBsssy3JZlnXBEO+fOtD7ceE734HDh0d8WWWRG4Cq+iiVYjz7bJg582gmnIiIiIiIiMQ1YwyeTv+RnmPhyE5LOppZdt998I9/nHxScjLceitceGHY84mIiIiIyPEGK65ugBuAZy3Lugr4JHCo9709QC4QBD4dyQWGJSkJcnJGfNm0ggxcFtHrW5aeDtu2RWcuERERERERCZu3u4eggay08HqWwQnBsu9+F2bNgosvPvnEL3857LlERERERORkA2aWGWMMcKZlWT8D3g38CtgHbADWAeuNMfEbKAP44x/h9ttHfFlKYgJT8tLZFa1gWR9joCdKfdJEREREREQkZH1lEx0pw9gXLDMG9uyBadP6PzEYhC1boKYm7DlFREREROSooXqWbQB+CewFioEXgRpgKXClZVklkV1emP72N7j33pAurSxys7OuzeEFDWLTJigqgmeeid6cIiIiIiIiEhKPrzdY5mQZxsOHwecbOFjW3Axz58Kf/hT2nCIiIiIictRgPcsSgaewSy4+DkwFzgXmYpdj/Chwb+958cnrhYyMkC6tKHJT3eAl0BN0eFEDTVgBLS2walV05hMREREREZGQeToDgHOZZS2dfqiutg+UlfV/Yn4+nHoqvPxy2HOKiIiIiMhRg5VhDBhjfg4cANzAeuBrwGRgGzADeNEYE4jGQkMSRrCsstCNv8ewr6nD4UUNICMDzjwTXnghOvOJiIiIiIhIyI6UYXSgZ1lWWhLdgSDdO3fZBwbKLANYutQOlgWjtLFTRERERGQcGPCuvrfE4oXANmPMc5ZlVQOfAP6GnVU2G/hxVFYZKq8XJk8O6dLKIjcAVXXtlBe6nVzVwJYtg5/8JKwgn4iIiIgMzhjDc2/V4bIsJmSnMjE7ley0JCzLcmwOn7+HfU0d7Gnwsrexg+pGL3sbvTR5/fzP1fOZOTHLsblEJDZaHe5ZBtB82XspPnA+FBcPfPLSpfD738Nbb8GsWWHPLSIiIiIigwTLgAnANMCyLOtJ7HKMTdjlGLdi9zB7JNILDEtXV1hlGAGq6ttZ6eSaBrN8Ofzwh/YuwRUrojWriIiIyLjy+t5mPvqn1487lprkYmJ2GhOy7OBZXxBtQnbake/z0pNxuY4G1Dq77YBYdYMdvYEQLgAAIABJREFUCNvT2Bcc81Lr8WHM0fFz0pMoy8/gUGsnn71/PY995hzSkhOi9SOLSAQ43bMMoLWrh+LS0sFPXrLEfl2zRsEyERERERGHDBgsM8a8CbxpWda1wO3AB4AngVOBs4ENwG3Y2WbxqaoKenpCujQrNYkJWalU1bU7vKhBLF0KX/gCDPVwJCIiIiIh+/ubNaQlJfDH68+ksb2b2tZODrX6qPX4ONTqY211E4c9PgJBc9x1yQkuirNTyMtI4XCrj0Me33Hv52UkU5afzlnl+UzNz6CsIJ2y/Aym5qeTk54MwIs76vnQH9bx/X9s43uXz43azxwLexu9PL3tMB89Z5qjWXsi8eJoz7LwyzDmpNvBstRf/BxOmQwf/vDAJ0+fDk8+CWefHfa8IiIiIiJiG85d/S1ADfAuYBHwFJBljNkWyYU5JiH0HbuVRW52RTNY5nbD7bdHbz4RERGRccbn7+HJTQd555wJnFWeP+B5PUFDY3sXta0+alt9HGrt5JCni0OtnTS0d1NZWUBZfjpTCzKYlp/BlPz0I5khgzlveiEfO3cav3upmvNOKWTl7AlO/nhx5Q+rq/nTK3t59/wSirNSY70cEcd5fH4ykhNITBiwFfiw9f39UXD372HJ4sGDZZYFF18c9pwiIiIiInLUkMEyY8yDlmXlAacZY16MwpqcEQzCf/0XvO99IT9IVBa5+esbBzDGRG83rN8Pr78OCxZAWlp05hQREREZJ1a9XYfHF+DyhYNn8ie4LIqyUinKSmV+aC1wB/Sli2bw8q5GvvK3TcyfnDNmA0lrq5sA2FXfPmZ/RhnfPJ1+R0owgh0scwV7SK2tgWnThr5g3z6491742MegoMCRNYiIiIiIjGfD3QJ3Jb3lFi3LSux7tSzrR5FaWNi8XvjjH2Hr1pCHqChy094VOKnETkQ984xdg/6VV6I3p4iIiMg48fD6GgrcKSytGDirLNJSEhO44z8W4vMH+cKDGwieUO5xLGjt8PP24TYAdtV7Y7wakcjw+PxkpToXLCtub8IV8ENZ2dAX7N8PX/ua3bdMRERERETCNmSwzLIsF/D/gN29h56zLOs9QBYwL4JrC4+396E8IyPkISoL3QDsPBzlvmUuF6xaFb05RURERMaBlo5unn+rnvcsKHGkbFo4Kgrd3PLuWaypauR3L+0e+oJR5vW9TZjeGGBUy5qLRJGnM0BWWvj9ygAyU5OY3HrY/mY4mWWnnw7JyQqWiYiIiIg4ZDifEnwW+Cdwfu/3HUAl8BcgfrfBOhEsK7KDZVXRfMDPyrIffF54IXpzioiIiIwDT26upbsnyBVDlGCMlmvOnMy75kzgx/9+m00HWmK9HEet29NEcoKLU4rc7G5QZpmMTa2dzmWWJbgsJvnb6ElIHF6wLDXVfm5UsExERERExBGDBsssy/p/wAzgm0CiZVnnATnAa8D3Ir+8MDgQLCtwJ5OdlkRVfZR3wy5bBq++Cp2d0Z1XREREZAx7ZH0NlUVuZpdkxXopAFiWxW3vnUthZgqfe2AD3q5ArJfkmHXVTcyblM2skixllsmY5fE517MMYN3p7+Cme16FiorhXbB0qd3v2hfFtgEiIiIiImPUgMEyy7LKge8AfzTGGCANOBfIBc7p/W9QlmUlWZb1+CDvp1qW9YRlWRsty7rHsp10bMQ/FYDfD9nZkJkZ0uW966OyyB3dzDKA5cuhuxvWro3uvCIiIiJj1P6mDl7b08wVC0sJ9fYyEnLSk/npNQvY0+jl1sdD77UbTzq6A2w+0MqiaXmUF7g52NpJZ3dPrJcl4jhPp59sB4Nl2WlJtHQF7bL8w7F0qf26Y4djaxARERERGa8GvAs3xuzGDojdYVnWO4B2Y8z3sXuXvQRUDTawZVlpwBvAikFO+yBwwBgzHzsIt2KAYyN3+unQ0gIXXRTS5X0qC93R3w27bJnds+yss6I7r4iIiMgY9eiGGgDes6Akxis52Vnl+Xx6eSUPvn6AJzYdjPVywrZhXwuBoGHRtDwqijIwBqpVilHGmGDQ0NYVICvVmZ5lAJ988jec9/jdw7/g4ovB44F58dtKXERERERktBh0y5oxZgdwEfADYEPv4TTs0owbgQG35RpjOo0x84ADg0zxDuDp3q+fw+6L1t+xmKksctPo7abZ2x29Sd1uO2CWmhq9OUVERETGKGMMf19fw6JpeUzKTY/1cvr1uQtPYcHkHG7++2YONHfEejlhWVvdhMuC06fmUl5g9wDeFe2y5iIR1t4dwBgcLcO45I1nKd07giyx5GRISXFsfhkfbnl0C996dEuslyEiIiISd4as72CMaQWuA5ZblpUIXGWM+V9gJ7AvzPnzgdberz1A3gDHRu6FF+Dqq+HQobAWWFlsP+BHvW/Ztm1w882qPy8iIiISps01reyu93LFwtJYL2VASQku7rh2IcbAjX/ZQE/QxHpJIVtX3cSskiwyU5OYVpCBZcHuemWWydji6fQDkJXqULCsu5uc5nr2ZhaO7LoHH7QzzMzo/TtDomttdROrdzbEehkiIiIicWdYxdCNMTuBa40xAWNMfe+xHmPMJ8KcvwHI7v06u/f7/o4dx7Ksj1uW9bplWa/X19f3P/LOnfDQQ3bvsjBUFvYGy6JdirGqCn74Q1i3LrrzioiIiIwxD6+vITnBxcVzJ8Z6KYOakp/Ody+fzWt7mvnV84NWPI9b3YEg6/c3s6gsH4C05ARKc9KUWSZjjqczAEBWmkNlGPfvxxUMUuUeYbCstRX++U/7+VFkGBrauznQ0klwFG/KEBEREYmEYXYOBmPM9gjM/yywsvfrdwDPD3DsxLXcZYw5wxhzRmHhAA8T3t7dqxkZYS2wNCeNtKSE6AfLzj0XLMvuXSYiIiIiIQn0BHl840EumFlEtoPl0iLlioWTuHxBCT9/didv7G2K9XJGbHNNKz5/kEXTco8cKy90s7tBwTIZW1qdziyrrgZgT2YRPn/P8K9bssR+XbPGmXXImBYMGpq8XXQHgjS0d8V6OSIiIiJxZchgmWVZq3pfJ1mWteiY42dZlvWT4U5kWda0fs6/Fyi1LGsT0IQdKOvv2Mi19z6Qhxksc7ksygszoh8sy82F+fPtcpIiIiIiEpKXqhpoaO/m8jguwXii71w+h5KcVD73wAY8vvCqJETba3vsAN+ZZUcrqVcUZrCrzqssBhlT+n43HetZ5vPRPqGU/dkTaOkYwe/9zJmQk6NgmQxLS6efvr+K9zd3xnYxIiIiInFmOJllvt5eZQ8ARcccLwWGbD5gjKnsfa02xnzphPe6jDGXGmPmGWOuM7aTjo3g5znK64WEBLvpcZgqi9zRD5YBLFsGL78MXdrxJSIiIhKKR9bXkJ2WxPIZIyxtFkNZqUn87JqF1Lb6+MbDWwj1djgW1lU3UVGYQb475cix8kI3nf4eDnnUi1fGjr6eZY5lrF56Kav+vY6a7KIjWWvD4nLZ2WUKlskwNB6TTXaguSOGKxERERGJP8MJlhng/cBfgdMsy/o/y7LSgIuAxyK5uLCkp0NlpV3KMEyVhW5qWjrxdgUcWNgILF8Oqamwa1d05xUREREZA9q7Avx76yEunTeRlMSEWC9nRE6fmsvnLziFxzYe5OH1NbFezrD0BA2v7Wli0bT8445XFNqVHnbXD7nPTmTU8Ph6e5Y5VYaRo4G3EQXLAC6+GKZPh0CUn1dl1Glo7z7ydU2LMstEREREjjVgsMyyrETLsm4GjDHmbmPMz4wx3wHuA54AJhhj3ojWQkfsG9+At95yZKjKIjcQgwf8Sy+FhgaYNSu684qIiIiMAf/ecgifP8gVo6gE47E+dX4li8ry+OYjW9jbGP+BprcPtdHmC7B4Wt5xxysL7XvpXfXqWyZjR19mmTs10ZkBP/hBZvz8NiCEYNmnPw2PPAKJDq1FxqxG77GZZQqWiYiIiBxrwGCZMSaAXWYx2bKsY2sZZgBZQFuE1xY3+oJlVfVR/pETE+1SkiIiIiIyYo9sqGFyXhqnT82N9VJCkuCy+Om1C0hwWXz2gQ34e4KxXtKg1lU3AnDmCcGywswU3CmJ7FawTMYQj89PZkoiCa7wK5kA8NxzpDc3ACEEy/qofL8MoaHN/jNSmpOmYJmIiIjICQYtw2iMuQPwA1+0LOt7lmV9DzgXeBeQZFlWeRTWGJqvfx0++1lHhpqan0GCy4pN37IHH4TTT4fu7qHPFREREREADnt8rKlq4IoFpVgOlOWOldKcNH545Tw27m/hZ8/siPVyBrVuTxOlOWmU5qQdd9yyLCoKM9ilMowyhng6A2Q51a+ssxNqa0mssB+vQwqWXXUVXHSRM+uRMavR243LgjmlWepZJiIiInKC4fYs+2+gEjhkjPmCMaYBeBC4JpKLC8urr8KbbzoyVHKii6n56bEJliUm2j/H669Hf24RERGRUeqxDQcJGnjPKC3BeKyL507kmjMm8+tVu6iqi8/iDsYY1lU3s+iErLI+FYVulWGUMaW100+mUyUY9+4FILmyAssKMVg2aRKsXatNljKohvZu8jKSmZqfQU1zJ8aYWC9JREREJG4MJ1iWbYzpAa4Hjr3z3gBcEJFVOcHrhYwMx4Y7pcgdm2DZeefZr6tWRX9uERERkVHq4fU1zJ+UTUVvv6xRbf9+vv3PX/DKLz9EwmWXwR13wPbtEEcfclY3eGlo7xowWFZemEFtqw9vV2B4A958Mzz+uIMrFHGWx+d3LrNszx4AXOXTyExJPNIPbUSWLAGfD9avd2ZNMiY1tneRn5HCpNw0ugJBGtoVXBURERHpM2SwzBiz1LKsImNMpzHmrmPeSge+GbmlhcnhYFllkZu9jR3R7xVRUABz5sALL0R3XhEREZFR6u1DbWyr9XD5aM8q68sQaW4m7b4/s7diDim7d8LnPgezZsHWrfb7+/ZBfX3s1gm8tqcJYNDMMrCDakPatQt+9CO7skIcBQRFjuXp9JPtVLAsKQnOOQcqKshOTwots2zpUvt1zRpn1iRjUqO3m3x38pFyuSrFKCIiInLUoMEyy7JSLMuaDTxgWdY8y7KmHfN2KfC0ZVklEV1hqCIQLAsEDXsbY9BrYdky+6HHH2KjZxEREZFx5JENNSS4LN49Pz5vUwdlDDz9NFx4IXzkI/axefPg4EE2/PwPLPnP33Jowzb4/e9h9mz7/e98B4qK4LTT4CtfgWeftTNMomhtdRMF7mTKC/q//y7vDZYNqxTjr38NCQlw6NDRKgsicabNFyAr1aFg2QUXwEsvwcSJZKcl0dIRQrZPSQmUlcHLLzuzJhmTGtu7yHenMCk3HYADzZ0xXpGIiIhI/Bgqs+y7wBLs8oulwK8sy3rUsqzzgQ8DtxtjDkZ4jaGZNg3Kyx0brrIwE4Cdh2NQivHSS+GKK6C1Nfpzi4iIiIwiwaDh0fU1nHdKAQXulFgvZ/h6euDBB+GMM2DlSti2Dc488+j7ubmsnD0BgH+1p8J//idYlv3eDTfA974HWVnw05/agbbTTjt67YEDEc/QWlfdxJlleVh9azrB1Px0XBbsqh9i45nXC3/4A1x5JcycCatXw9tvR2DFIuHxdPrJSnOoZ9kxstNCzCwDu3zpVVc5uyAZUxrbu8nPSKY0ty+zTMEyERERkT5DBcu+AdwNJALVwG+BZOARIMEYc0tklxeGZ5+FW291bLiKInuXbEz6lr3znXDPPXZJRhEREREZ0NrqJg62+kZfCcbbboNrroH2dvjd76C6Gm688bhTphVkcEqRm6e2HT7+2vnz4etft3vcNjXBE0/ALb236cGgHTirrISamogs/WBLJweaOwcswQiQmpTA5Lz0oTPL7rsPWlrsAOBVV9kBwb/8xeEVi4SnJ2ho63I4s+yTnwTCDJZ9/OP23yMi/fD5e2jrClDgTsadkkhuepLKMIqIiIgcY6hg2aPAc8Bs4EagHDuAlgc0WZb15cguL36kJydSmpNG1XBKx0SCMVBbG5u5RUREREaJR9bXkJGcwMpZE2K9lMG1tMAPfmAHuMDOFPvb3+yMsv/6L0jpPytu5exi1lY3DVymze2GSy45+oF5Tw/88Id2oOyrX3X+5+Bov7IzywYOlgGUF2Swe6jMstxcuPpqWLIESkvh3HPhgQfUu0ziSrsvAECWUz3LNm488mc8Oy2Z1s5AaOMYAzt22H3/RE7Q6LX/3ejLui7NTaOmRZllIiIiIn0GDZYZY95ljFkKbDDGfAKYiV1+8UfAncBllmUVRX6ZI9TZaZetue8+R4etKHLHJrMM7A83pk+HQIgPTiIiIiJjnM/fwz821/LOORNJS06I9XL6V1MDN90EU6bY2WBPP20fLymB977X7tU1iJWzJtATNDz3Vt3w5ktKsgNxX/gC/PnPsHZtmD/AydZWN5GZksjMiVmDnldR6GZ3fTvB4CCBr/e9z84k6yvneO21sH07bNni4IpFwtOX+ZWV6kAZxrY2aGy02whgZ5Z5Ov2YUALEwaD9HPyTn4S/LhlzGtu7AMjvDZZNyklXGUYRERGRYwyVWdan7059DvAT4AngW8ByY8wwn9SjqL0dXn/dLkPjoMpCN7uGesCPlNNPt3+uN9+M/twiIiIio8Cz2+to6wpwRbyWYLzzTrun7v/8j92Tdv16+P73RzTE3NJsJmSl8tTWw0OffKybb4YJE+Dzn3c8S+u16iZOL8slwdV/v7I+5YVuugLBgTMZ/v1vu2fZsd73PvjKVyAnx6HVioTP4+sNljmRWbZnj/1aVgbYwbLuniA+f3DkYyUkwFlnwZo14a9LxpzGdjuzLN+dDMCk3DQONHeEFpgVERERGYOGGyybbFnWfwK5wFLsvmWfM8bEZ5pT30N2Roajw1YWufH5B3nAj6Rly+zXZ5+N/twiIiIio8DD62sozkrh7Ir8WC+lf8bAypVQVWVXQFiwYMRDuFwWK2YV88KOenz+nuFfmJlpB+kuu8zRSgVN3m521rUP2q+sT0WhfW++u6GfUowHDtjlI08MHhYW2mUkJ092YrkijvD0ZpZlOxEsq662X4/JLANC71u2dKmdidnaGv7aZExp6M0sK8jozSzLTcPnDx4pzygiIiIy3g03WPYz7OyyH2H3K3sn8JhlWb+3LMuB2hMOi2CwDIhN37LiYli8GO6/P/pzi4iIiMS5Jm83q96u4z0LSofMcIqqzZvhySftrz/5SXj00SMfiofqotkT6PT38NLOhpFd+B//YWeYJTnUZ4mj/coWDydY1nsvvau/sua/+Y1dQu7jHz/5vUAA/vUv2LkzrLWKOOVIZlmqA79LBQV2udGKCsChYJkx8Oqr4a9NxpS+oNjRzLJ0AJViFBEREek1rGCZMeb3xpg/GmP+zxjzK2PMF4DTgMfjMrusL1jmdjs67CmDPeBHw4c+ZH/gsnFjbOYXERERiVNPbjpIIGi4fEEclWC85x57s9ONN9oBH8sC13D3qg1scXkemamJPLX1UGgDPPQQ/PKXYa8DYF11EymJLuaWDl0mMT8jmazURHY3nHAv3dUFd90F7373kVJ0x2lrszPifvtbR9YsEi5Pp/0InJXmwL7RJUvsDZH5dkZs2MGyxYvtv2dUilFO0NjeRWqSi/Tenp6luWkA1ChYJiIiIgIMP7PsJMb2iJOLcUxKir2jrrjY0WFzM5LJz0imKlbBsmuvtRueT58em/lFRERE4tTD62uYUZzJzImZsV4K+HzwiU/YG50WL4YXX4RE54oxJCW4uODUIp7ZfphATwh9jf7+d7jpJti3L+y1rKtuYuGUHJITh36ssCyLiiI3u+pOKMP44INQXw833ND/hbm5cNFF9n1wMISfV8RhjvYs8/mO+7YvWNbSEWJpPLfb7v/3mc+EuzIZYxrbu8nPSMGy7OzrvmDZgeaOWC5LRIaptcPPvkb9voqIRFL4W1vj0fz5sHo1nH6640NXFLnZGatgWV4eXH01pKXFZn4RERGROLS30cub+1q4fGHpkQ8BY8brtTdt3XUXfPWr8PTTMGGC49OsnD2B5g4/b+xtHvnFP/qR/frVr4a1hvauAFsPtrKobOgSjH0qCt3sOrGk+UsvwamnwgUXDHzhtdfafc1eeSXE1Yo4x9Ppx7LAnexAEPyss+Caa458G3ZmGcCFF0JRUbgrkzGmwdtNQW8JRrDLiGanJakMo8gocevjW7ni12vwh7JRSkREhmVsBssiqLLITVVdO8aY2CygvR1+8AP7QwURERER4ZH1B7EseM+Cklgvxe6Ze8EF8NhjcNttjmaUHeu86YUkJ7p4atvhkV88ZYqdWXb//fDyyyGv4Y29zQQNLJqWP+xrygszqGvros13TCDgrrvsknGDBTovuwxSU+GBB0Jer4hTWjv9ZKYk4gq3P6IxUF19XEUUR4Jl9fVw++3q8yfHaWjrosCdctyxSblpyiwTGQWCQcMLO+pp9HYf6RcrIiLOG5vBsgcfhFmz4FCIfRwGUVnoprXTT0N7iGUxwpWUBD/5Cdx5Z2zmFxEREYkjxhgeXn+As6blU5ITo+z7QAC+/nXYsMH+/r//2+6/FUHulETOqSzgqW2HQtvE9eUvQ0kJfP7zIZc2XFfdSKLL4rSpQ/cr61NRaPcA3l3fW4qxszejIW+I7LTMTLjkkrCCeyJO8fgCzpRgbGkBj+e4Xn2ZqYlYlp29FrLOTvjSl+Bf/wp/jTJmNHq7yD8mswz6gmXKLBOJd28fbqPRa38O+dTWEDZKiYjIsIzNYNmhQ7B9ux1Yclhlkf2AH7O+ZSkpdpmORx6xm52LiIiIjGMb9rewp7GDKxaWxmYBtbV2JtkPfmBnk0XRylnF7G/q5K1DIdwTut3wq1/BF74weEbXIF6rbmZ2aTbpIyhFV1GYAcDuhnaoq4OJE+Hee4d38V13wWuvhbJUEUd5Ov1kpTrwrFldbb9Om3bkkMtlkZWaFF5m2ZQpMGmSnbEpgr2xpLG9m/wTMstKc9KpaemMXeUcERmW1TsbAJhbms3T2w7rd1ZEJELGZrDM27tTNSPD8aGPBMtO7LUQTR/6kL1b8G9/i90aREREROLAI+trSEl08c65zvcFG9KqVbBwIbz+Otx9N3zrW1Gd/oKZxVhWGDuML7/c7gUWQrDM5+9hw/4WFk8bfr8ygCl5GSS4LHbVeeF3v4PW1uH3Gc7LA9fYfHyR0cXj8x8plxiWvmDZMZllYJdiDCtYBnbvRGViSi9PZ4BA0JCfcXJmWUd3D80dYf55E5GIWl3VQEVhBtedNZWalk621XpivSQRkTFpbD5ter32g3RKytDnjtDE7FQykhOoOhzDrK6zzoLKSvtDGREREZFxyt8T5PFNtVw4q9iZLI+ReO45O6MsJwfWroXrrovu/EBhZgqnT8nlqW1hlB43xi4bedttI7ps4/4WunuCLCobWbAsOdHF1Lx0qg+12GXFV6yAU08d/gB//jPMmwd+fbArsePpDJCV5kA/wooKu39gRcVxhx0Jli1ZAvv32//JuNfg7QLot2cZoL5lInGsK9DDuuomzqks4B0zi8LbKCUiIoMau8GyjIyQS8oMxrIsTp2YxfbaGAbLLAuuv94un6MPCkRERGScenFHPU3ebq5YEIMSjOeeC7fcYpcFnDMn+vP3Wjm7mK0HPaF/0GlZsGkT3Hor7Nkz7Mv6msufUZY74inLCzOY8Py/oaYGbrhhZBdnZ8PmzfDMMyOeV8QpHp9DZRgXLLCD1VlZxx12LFiWmAjbtoU3jowJjb0910/uWZYOoL5lInFs/b4WOv09LK0soMCdwhlTc3lqm4JlIiKRMDaDZdOnw8UXR2z4OSVZbD3YSjAYwxrBX/ua3RcjAn3ZREREREaDh9fXkJuexHnTC6M36T//CXv32vdg3/oWZGZGb+5+rJxll598OpwPTW67za7K8OUvD/uStdVNnDohk5z05KFPPkFFoZuVz/8VU1Y28nv2lSvtbL4HHhjxvCJO8XT6yXKiDOPevdB+cnl/R4JlCxeCxwMXXRTeODImNLbbmWX5GSf0LFNmmUjcW1PVQILL4qyKfMC+99te62F/k35vRUScNjaDZZ/8ZEQfoGeXZuPt7mFPozdicwzbgQN2+RwRERGRcaTN5+fpbYd59/wSkhOjdEvb3Azvf//Is6EiqKwggxnFmeGV45k8Gb7yFXjoIXjppSFPD/QEeXNvM2eOsARjn/LCDL560Weo+59fQULCyC5OSYH3vhcefhh8vpDmFwmHvyeIt7vHmcyyd73L7kd9giwngmUJCZCWFt4YMmY0eO3MsoLM4zc4ZKclkZmaSI0yy0Ti1uqqBuZPyj7y786KWcVAmBulRESkX2MzWBZhc0qyAdhc0xrbhTz2mP3hxhtvxHYdIiIiIlH2zPbDdAWCXDa/JHqT/vd/Q2srfPe70ZtzGFbOLmbdniaaez8MDclNN8GkSXDjjUNuxNpW68Hb3cOiaaEFyyoK3VTnlbJt5hkhXc+110JbG/zrX6FdLxKGNl8AIPyeZcbYpU+nTTvprb7MMhPupsjHH7ezMVW6f9xraLMzy/L6yQaelJuuMowiccrj87NxfwvnVBYcOVZWkMH0Ynd4PWtFRKRfYzNYdtVVcOWVERv+lGI3yQkuth70RGyOYTn3XHt37T33xHYdIiIiIlH25KZaJmanctqUkffMCsnBg/Dzn9uZZfPnR2fOYVo5awI9QcOzb9WFPkh6Ovz+9/CLXwzZ93ddtd2vLKRgWXMz8770/zilfi+76k8uPzcs558Pn/oUTJ0a2vUiYfD0ZnyFnVlWVwednVBWdtJbOelJ+HsMnf6e8OZob4enn4YtW8IbR0a9Rm8XuelJJCac/BHQpNw0BctE4tSruxoJGlh6TLAM7Hu/ddVhbpQSEZGTjM1g2YEDdn32CElKcHHqxEy2xDqzLDcXLrsM7r9fuwVFRERk3Gjt9PPCjnoumTsRl2vwwI5jbr0VAoG4yyoqUaDPAAAgAElEQVQDmFOaxcTsVJ7aGuYO45Ur4eyz7a8HyWhZV93E1Px0irNSRz7HH/9I8t8eIi/ZYld9iCXNExPhV7+yezKJRJnHZz93ZYfbs6y62n4dILMMCL8U4+LF9uvateGNI6NeY3s3+e6Uft+zg2Ud4Wcyiojj1lQ1kJaUwMITNoetnF1M0MBz4WyUEhGRk4zNYJnXCxkZEZ1iTmk2W2paY39Ded11UF8P//53bNchIiIiEiVPbT2Ev8dwybyJ0ZnQGLv/z2c+0+8H27FmWRYrZxXz4s56OrvDzEQJBu2srW9+c4C3Da/taWJRKP3KenrsINc559Azb37omWVg/z/ZsMH+TySKPJ19ZRhHQbBs2jQoKIB168IbR0a9xvZu8jNOLsEIdhlGb3cPLR3agCsSb1ZXNbC4PO+k/rxzS7OZkJWqUowiIg5TsCxEc0qy8fgCsS9X8M532g9AKsUoIiIi48STm2uZlJvGgsk50ZnQsuDXv4bbb4/OfCFYOXsCPn+Ql3bWhzeQy2XfS//4x7B790lvV9W309zh58xQSjD+61/2mDfcQEWhm93hBssuucTO+BOJor7MsrB7lp1xBtxxx+DBsnCDF5YFixYps0xo8HZRMEBmWWlOGgA1LSrFKBJPals72VXvPa5fWR/Lslgxq5gXdzTgC7dkr4iIHKFgWYjmlGYBxL4UY1ISPPSQ/aAlIiIiMsY1e7tZvbOBS+ZNxBqit5YjNm8++kFzNOYL0aJpeWSlJvLUtsPhD/aDH9ilDm+66aS3+vqVLQ4lWPbLX0JJCVxxBeWFGTS0d4ceDHC54Oqr4R//gNYY34/LuOJYz7JTToEbbrD7BZ7AscwygBUr7L5oPfowdTyzyzAOlFlmB8sONHdEc0kiMoTVOxuAk/uV9Vk5u5hOf8+R80REJHxjM1j2nvcc7bcQIdOLM0l0WWw5GAcP58uXQ3FxrFchIiIiEnH/3nqIQNBw6dySyE9mDHz+83aPWJ8v8vOFISnBxQUzi3l2+2ECPcHwBisthZtvhr//HVatOu6tddVNFGelMCXv5A/4B2WM3T/p5pshKYmKQjcAuxrCyC675hro7oZHHw19DJER6gtghV2G8bXXjpZiPIGjwbLPfx6efNIuJSvjUncgSGunn/yM/jPLJufaf5/HvGqOiBxnTVUDBe5kZhRn9vv+4mn5ZKYmqhSjiIiDxmaw7Le/heuvj+gUqUkJnFKcyZYaT0TnGbbHHoMbb4z1KkREREQi6snNtUzNTz+S5R9RTz8Nzz0H3/gGpKZGfr4wrZxVTHOHn9f3Noc/2Be/CFOn2sGtXsYY1lU3cWZZ3siz+iwLvv1tu+8bUF5oV4HYXe8NfY2LF9trfOCB0McQGSGPz4/LgozkMINP73//cb9fx8pyMljWR5ll41ZzRzcABZn9Z5ZlpSWSmZKoYJlIHDHGsLqqkSUVBbhc/d9zJSe6OH9GEc9sr6MnaKK8QhGRsWlsBsuiZE5JFltqWjEmDv5R2rIFfvazAXcnioiIiIx2je1dvLyrkUujUYIxGISvfMXuJ/SJT0R2Locsm1FISqKLp7Y6UIoxLQ3uu++4QNSB5k4OeXwjL8HY1gaPPAKBwJFDk/PSSUqw2BVO3zLLgmuvhZdfhg6VD5Po8HQGyEpLCu/voJ4e2LvXLo/Yj8yURCzLwWDZpZfaZUtlXKpv6wIYMLPMsixKc9NUhlEkjuw43E5De1e//cqOtXJ2MU3ebt5wYqOUiIhEJlhmWVaqZVlPWJa10bKse6x+niQsy1puWdbq3v/2W5b1YcuyzrQs68Axx2eMePKGBvvh/ne/c+RnGcyc0mwavd0c8sRBWZ4PftB+/fOfY7sOERERkQj519ZD9AQNl0SjBONf/gIbNsB3vwvJ/e/GjzfpyYmce0oBT2075MxmriVL7Mytffvg619nx+PPYpkgi6blj2yce+6BK66AN944cigpwcXU/Ax21YURLAP48pehpqbfvk8ikeDx+Y+USQxZbS34/XYwvh8ul0VWapJzwbLcXHjlFbscqow7jd7ezLIBepaB3bdMmWUi8WN1VW+/slMGD5Ytm15IcoKLp1WKUUTEEZHKLPsgcMAYMx/IBVaceIIxZpUx5hxjzDnAJmB977l39h03xrw94pm9XrunRBRqsveV/4mLUoxTpsD558Pdd+shSERERMakJzbWUl6YwcyJ/fducFR7OyxbBv/xH5Gfy0ErZ03gQHMn22vbnBt03Tr40Y+44COXsfbXH2H6t74I//gHdHUNfa0x8Mtfwumnw6JFx71VXpDB7oYwyjAC5OVBRkZ4Y4iMgKfTT1ZqmMGyvmogA2SWAeSkOxgsW7zYDtAdOODMeDKqNLb3Zpa5+88sA5iUm05Nc2d8VM0REdZUNTCtIIPSnLRBz8tMTeLsinye2nZYv78iIg6IVLDsHcDTvV8/B5w/0ImWZaUDlcaYTdjBsisty1pnWdbf+stIG5K394E7Cg/NMydm4bJgS01rxOcaluuug6oqWLs21isRERERcVRdm4+11Y1cOq8k8iUYAT72MXj+eXCNrqrlF8wswmXBv7c6uMP4fe+Dujq+f+3X2HfqQqz777fLurX23gO//bZd3aE/zz8P27fDDTfYZROPUVHkZm+jl0BPMLz1vfSSHYw7pF3VEnkeX4CstMTwBtmzx34dILMMIDvN4WAZ6DlxnGpstzPL8ofILGvrCuDpDAx4johEh78nyKu7G4cswdhn5exi9jZ2sONwmNn6IiISsWBZPtAXQfIAgzU2WAE82/t1FfBNY8wiYCKwbMQzRzFYlp6cSEWhm60H4yRYduWVcPbZ6tkgIiIiY86/thwiaODSeRMjO1F7Ozz0kN2zLBpBOYflu1M4Y2oeT21zoG/ZMeqS0vnd1CW8eftv7cDYmjVQVGS/+dnPQnExnHce3H67vXmrzy9+AQUFcM01J41ZXpCBv8ewP9zSX/n58Oab8Ne/hjeOyDA4kll24YXw8MN2mdMBOBosmzfPLie7bp0z48mo0uDtIjnBRWbKwEHeSbl29sp+9S0TibkN+1vo6O5h6TCDZStmFgOoFKOIiAMiFSxrALJ7v87u/X4g7wae6P16D/DMMV8X9XeBZVkftyzrdcuyXq+vrz/+zSgGy8DuWxYXZRgBsrLsBufveEesVyIiIiLiqCc21jK92M304giXYPzpT+Hqq2HjxsjOE0ErZxezvdbD/ibnPvR8rdpuHL9oWj6kpNgbtPrcdht8/et2ptmXvgSnnAIf+IBdGn3rVjtLLzX1pDEritwA4fctmzUL5s6FBx4IbxyRYWh1Ilg2cSJcfrn9uzSALCeDZSkpcPPNsHSpM+PJqNLY3k2+O3nQrOxJuXbfR/UtE4m91TsbcFlwdvnwesQWZaWycEqO4xulRETGo0gFy54FVvZ+/Q7g+f5O6i2zuBy7VCPAF4BrLctyAXOALf1dZ4y5yxhzhjHmjMLCwuPfLC6GT3zC7uEVBbNLsjjk8VHfNoyeDdHS1gZ798Z6FSIiIiKOONTq47W9TVwytySyE9XXw49/DO99LyxcGNm5ImjFLHuHsZMfmqyrbiQ9OYHZJVknv3naafCd79gBxupq+PnP4bLL7ADZW2/BN77R75gVBb3BsnoHygZde62d7bZvX/hjiQzC4/OHX4bxsceGzPLKTkvC41SwDODb34b3vMe58WTUaGzvGrQEI3CkL1JNi4JlIrG2pqqBuZNyyE4f/saMFbOK2XSglYP6HRYRCUukgmX3AqWWZW0CmoBdlmX9pJ/zzgS2GWN8vd//ErgeWAs8bIzZNuKZZ86E3/wGKipCW/kIzSm1E+jiphSjMbBgAdx4Y6xXIiIiIuKIf2yuxRi4dH6ESzB+//t2lYLvfz+y80TY1PwMTp2QyVMO9i1bt6eZ06bkkpQwxONDWZldlrGv7KLLBenp/Z6anZ5EgTuZ3fXe8BfYN9+DD4Y/lsgAugI9+PzB8DPLPvtZuOOOQU/pK8NojAlvrj7GwO7d0NTkzHgyajR6uylwD5zFCJCTnkRGcgIHVIZRJKbafH7W72/hnMrhZZX1WTlrAgDPbFd2mYhIOCISLDPGdBljLjXGzDPGXGeMqTbGfKmf89YZYy475vtaY8xyY8yZxphbQpo8ELB7TETJrN7dtVsPxkkpRsuydww+8QQ0NsZ6NSIiIiJhe2LTQWZOzKKi0B25SfbsgTvvhP/8Tzj11MjNEyUrZxXz2p4mmrzdYY/V2uHnrUMeFk0brA1xaMoL3c5kllVU2AGImTPDH0tkAG2+AMCIdvufxO+H/fth2rRBT8tOS8LfY+jo7gl9rmPt3m3/nqi337jT0NZFfsbgwTLLspiUm64yjCIxtnZ3Ez1BM+x+ZX0qi9yUF2bwtEoxioiEJVKZZbFz552QkGCX0YmCrNQkyvLT2XwgTjLLAD70IfshTDtrRUREZJSraenkzX0tXDovwlllNTV2r61vfzuy80TJytkTCBp41oEdxq/vbcIYOLPM+WBZRaGb3Q0OZJaBXf7xkkucGUukH31lEcPKLNu/397cOYxgGeBc37LycsjLG7L8o4wtxhgavN0UDFGGEWBSbpqCZSIxtrqqgdQkF6dNyR3xtStmFfPKrkbn/t0QERmHxl6wzNv7sJ2REbUpZ5dmsyVeyjACzJ8Pc+bA3XfHeiUiIiIiYfnHplqAyAfLli6FzZuhtDSy80TJ7JIsSnPSHOlbtm5PE0kJFgun5DiwsuNVFGbQ5O12JAMOgIMHFQyQiPH0ZpaF1bNszx77taxs0NMcD5ZZFixaBGvXOjOejArtXQG6A8Ehe5YBlOamqQyjSIytqWrgzLI8UpMSRnztylkTCAQNq96ui8DKRETGh7EZLLMsSEuL2pRzS7M50NxJS4dDD/nhsiw7u+zVV+0m6yIiIiKj1BObDjK3NJup+RHcCPXQQ9DZad9DjRGWZbFiVjEv7aynM8wybuuqm5g/KSekD26G0ldac7cTpRgBrr0WPvpRZ8YSOYEjmWV9z2dDZJblOB0sA1i8GLZuhbY258aUuNbYbn9GMVQZRrAzy9p8AWWliMTIYY+PnXXtnDPCEox9Fk7OocCd4shGKRGR8WpsBsvS06P6YceckmwgjvqWAVx/PWzaNORDmIiIiEi82tfYwcYDrVwSyayyl16Cq6+G3/42cnPEyMrZxfj8QV7cGXp58o7uAJsPtHJmBPqVAZQX2kHQ3fUOlWK8+mrYssUOCIg4rC+IkJUWRrDs6qvhjTdg8uRBT8uKVLDMGHt+GRcavV0Aw8osm5SbDkCNSjGKxMSaqgaAEfcr6+Ny2RulVr1VR1fAoX6XIiLjzNgMlkWxBCPYZW4AttTEUSnGggKYOzfWqxAREREJ2ZOb7RKMl8yNULDMGPjKV6CkBD7+8cjMEUOLyvLITkviqa2h7TD2+Pzct3YfgaBhUYSCZZNy00lOcLHLqcyy970PXC74y1+cGU/kGB6fA5llmZlw2mmQOHgpR8fLMAIsWWL3tZ43z7kxJa419GaWFbiHl1kGqBSjSIysrmogNz2JWROzQh5j5axivN09vLyr0cGViYiMH2EUW49TK1YMuUvPabkZyZTmpLElnjLLwO7Z8OUvw6c+ZT8YiYiIiIwiT2w6yILJOUzOS4/MBI89Bq+8AnfdZVcmGGMSE1xcMLOIZ986TKAnSGLC4PvkjDFsq/Ww6u16XthRz5t7mwkEDVPy0jmzLDLBsgSXxbSCDOeCZRMmwPLlcP/9cOutY6q0psSep9OBnmV33QVTpsA73znoadnpSb1zOhgsy86Gq65ybjyJe40jCpbZ/w4eUGaZSNQZY1hT1cCSygJcrtDvXc6uyCcjOYGnth7m/BlFDq5QRGR8GHvBsve9LybTzinNYms8ZZaB/TD0yCP2hz8KlomIiMgoUt3gZetBD9+4ZGZkJggE4OabYcYMu3z1GLVy1gT+/mYN6/Y0saTi5LI+LR3dvLSzgRd22AGy+ja7ZNfskiw+fl45y2cUsXBKDklDBNrCUV6YwduHHOyh9IEPwMc+Btu3w6xZzo0r457H5ycpwSItnP593/62HSgbIljmTk7EZTmcWQawYwesWjUms2nlZI3t9t/peRlDl2HMTU8iLSlBwTKRGNhV385hTxfnhliCsU9qUgLLZxTxzPbDfD84J6zAm4jIeDT2gmUtLZCcHPXdwXNKsvn31sO0+fxkhlOWw0kZGXDllXapjTvugNTUWK9IREREZFie3HQQgIsjVYKxoQHy8uDGG4cshzaanTe9gJREF09tPcySigKCQcPmmlZe2FHPqrfr2LC/haCBnPQkzj2lkGXTCznvlAKKsqJ331hR6OapbYfpDgRJTnQgKHfNNbByJUyaFP5YMqY8uamWxeV5w8qy6Y+n009WahJWqBmLPh/U1kJZ2ZCnulwWWWlJzgfL/vlP+Pzn4ZJLoLTU2bEl7jS0d5GVmjisv1sty2JSbho1LSrDKBJtq3eG16/sWCtmFfPk5lo2HGjhtCm5YY8nIjKejL1PBi65BNLS4JlnojrtnNJsALYd9LC4PD+qcw/quuvg7rvh8cdVckNERERGjSc21XLG1FxKctIiM8GECfDSS5EZO46kJydy7imF/GNzLS0d3by4s4EmbzeWBfMm5fCZd5zC8hmFzJ+UQ0KMdh+XF2bQEzTsa+qgssgd/oAZGVHvYSzxr6G9i0/f9ybnVBZwz0cXhRTw8vgCZKWFsTFy7177ddq0YZ2enZZES4fDwbLFi+3XtWvhve91dmyJOw3e7hEFhyflpimzTCQGVlc1MjU/3ZHS4+fPKCLRZfHU1sMKlomIjFDk6qnEitcbk4fj2aV2A86461t2/vl20/q77471SkRERESGpaqujbcOtXHJvAhllb3xht3b1bLGRU+rd8+fSF1bFy/tbGDZ9EJ+fu0CXv/6hTz66aV8YcV0TpuSG7NAGdiZZYBzfcsAmprsMnd//rNzY8qotq/JzpZZXdXA396sCWkMO7MsjP2me/bYryMIljmeWbZgASQl2cEyGfMa27vIdw9dgrHPpNx0BctEoizQE+TV3Y2OZJWB3fPyrPJ8ntp2yJHxRETGk7GXWRajYFlRZirFWSnx17csIcEus9HcDMaMiw+EREREZHR7YlMtlhWhEozGwEc/Ci4XvPmm8+PHocvml7Bwci6TctPisndFeaF97+5osCw3F3btgv/9X/jgB50bV0at/b3Bskm5aXz3iW0sm15IYebIyjG2dvqdySwbRhlGiFCwLDUV5s+HdeucHVfiUmN795ENCcMxKTeN1k4/Hp9dclREIm/jgRbauwKc41CwDGDl7GK+9ehWqurancnaFxEZJ5RZ5qA5JdlsORhnwTKAm26CH/wAenrgM5+Bv/7VDp6JiIiIxBljDE9sqmVRWR7Fkeib9eKLsHEjfPKTzo8dpyzLYkp+elwGygAyU5Moykxhd73XuUEtC66/Hl54AXbvdm5cGbX6smV+88HT6ezu4TtPbBvxGGEHED72MTh82K78MQzZaUl4nA6WgV2Kcf16CAadH1viSqO3e0SZZaW5dunjGmWXiUTN6p2NWBac7WBLlwtnFgPw9LbDjo0pIjIeKFjmoNml2VTVtdPZ3ROT+Ye0ezfcc4/du6ygAM4+G265RR8giIiISNzYcbidqrp2Lo1UCcaf/xzy8uADH4jM+BKSikK3s5llAB/6kJ1B+H//5+y4Mirtb+qgwJ3MnNJsPvOOSh7feJBnt4/sQ0RPZ4CstDCKs1gWFBXZfy6HISKZZQDf+hYcODDsdcjoFOgJ0tzRTf6IepbZ/ZIULBOJnjVVDcwpySY3Y/iB7aGU5KQxtzRbpRhFREZo7N0df+MbcOmlMZl6TkkWQQPbD8VZ37I+06dDYyOsWQPf/KZ97HvfO1o7f9MmuPNOBc9ERETC9NLOetbvUxZ3KJ7YdBCXBe+cE4Fg2Z498Oij8PGPQ3r4DdTFORVFGeyu92KMcW7QSZNgxQo7WNYTp5vZJGr2N3ccCQT8v2UVTC92841HttDeFRj2GGFnlt16K9x777BP7wuWOfp7AXbAzq2yXGNdc4cfY6BwRD3L7MyyA80dkVqWiBzD2xXgzX3NjvUrO9bKWcVs2N9Cncfn+NgiImPV2AuW3XQTXHhhTKaeU5oNEH99y46VmAhLlsC3vw2vvAINDXDuufZ7jz8On/oUVFRAZaX99SOPgD8CuxlFRETGIGMMP3tmB9f9fh1ffGhjrJcz6vSVYDyrPH/EvYSG5YUXICnJvseRuFJe4Ka100+jt9vZgW+8EW64Qfezwv6mziOBgOREFz+8ch6HPD5+/K+3hnW9z99DdyAYXs+yX/7SLgU7TNlpSQSCho5IVC758Y/hjjucH1fiRqO3C2BEmWX5GcmkJrmOlC0VkchaV91EIGgc7VfWZ8XsYoyBZ7bXOT62iEReT9Dwi2d38tn71zu/cUoGNLaCZYGAnRXldbDfwQhMzE4lLyOZLTVxmlnWn9xc+0MjgK99Dd56y35omjkT7r4bPvIRu1yIiIiIDMrn7+HGv2zgZ8/spCw/nd31XvY2xuaeZLTaVuuhusHLpfOG189nxD78YaipgcmTIzO+hKyit/n8rjqHSzFedJG9mS41Av3vZNToCRoOtnQyOe9oRulpU3L58Nll3P3qXt7Y2zTkGB6fHXANOVjW3m5vVCwrG/Yl2b1zRaQU47PPwh/+4Py4Ejca2uzNB/kjKO1mWRaTctMVLBOJktVVDSQnujijLNfxsWcUZzIlL/1oKcamof+tE5H40NjexUf+uI7bn97BYxsPsr9J/y5Hy9gKltXW2llR998fk+kty2J2SRZbDsZxZtlgLAtmzLB33z7+uP0P6Zo1djaazwd33QWKZIuIiJyksb2LD/7vWh7ZcJCbLprB/12/CIDn39JOzpF4YlMtCS6Ld86Z4PzgHb0lpfKda54uzikvsHsO726IQIC5s9Mufdes0qjj1SGPj0DQMDn3+PKrX7poBiXZaXzlb5vpCgyeveXptMs1ZqWG2LOsr/T9tGnDviSiwbJFi2Dz5phtNJXICyWzDKA0J40DLSrDKBINa6oaOLMsl9SkBMfHtiyLlbOKebmqEe/+gzB3Lnzuc9DtcBa/iDjqjb1NXHLHatZWN/Ff59j3jev36zkmWsZWsKzvRj8jI2ZLmFOazY7DbUM+bI0Kyckwe7b99X33wSc+Addfb2fwiYiICABVde1c8euX2VzTyq/efxqfPr+SsoIMygsyeP7t+lgvb9SwSzAeZElFPnkONjgHIBiEM8+EL33J2XHFMaU5aaQkupzPLAPYvh0++MGYbaiT2NvfZH/wPzkv7bjj7pREvnfFHKrq2rlz1a5Bx+gLWIWcWVZdbb+GECxr6YhAsGzxYvvvxjfecH5siQsN7fYH4gUj6FkGdt+yGmWWiURcXZuPtw61RaRfWZ8Vs4rp7gnyQl0Arr7ariR1/vl2pQURiSvGGH6/upprfvsqyYku/v7JJXz1XaeSmuRiw/6WWC9v3BhbwbL23ofrGDYrnluajb/HsONQBB70Y+n66+0+Z3/6E1xxxdHd2SIiIuPYmqoGrvj1Gjq6e3jg42dxybyJR95bPqOIV3Y30tGtTSbDsbmmlf1Nnbw7EiUYn34atm2D+fOdH1sc4XJZlBe6I5NZtnCh/f/+j390fmwZFY4Ey07ILAM4f0YR71lQwq+er2Ln4bYBxzhShjE1xGBZczOkpIwoWFbWm3EZkQ9IFtkZ0Kxd6/zYEhca27tIdFkj/jM7KTed5g4/7V26fxGJpFd2NQJwbmVhxOY4fWou33zlXjy/uQt++lN44AHYuBFOOw2efz5i84rIyLT5/Hzq3jf57hPbOP/UIh6/4RzmlGaTmOBibmk2GxUsi5qxFSyLh8yykmyA0VuKcSCWBbfc8v/ZO+/oqKq9DT8zk94T0hu9pUAoAtJBQFAUbCiK8mFDRfSqF6+9Ye+9YC+IIiogiBQBQXogAUIPAVJJ720yM+f7YyfUlClnSEj2s1ZWSOacfXaGmTl7/8r7wscfw/LlMG6clLKRSCQSSZvmp+2pTP9qOyHeLiyeNZg+kWd7DYzuEYjeYGJzcn4zzfDiYtmeLBx1Gi6PtoME4/vvQ1CQqKiVtFg6BbhzNNcOBWcajSj8io8XsnOSNkdaYSUaDYT6uNb7+DMTo/BwduB/v+7BZKpfdr6ktrPM29VKGcbbbhMFhwHmB0VDfVzpHeHDiqQs667ZGAEBIpEsiyBbLfllevzcndBqLfMgD/cV7xPZXSaR2Jd/j+Th4+ZIVKiX3a7hkJ/H9M2LMO7ZS43RBDfeCNu3g5+fSJ5JJJJm50BWCVd/uIlV+7N54ooezLu13yl1AYC4CB+SMkvQG0zNOMu2g0yWqUyEnyueLg4kZbSyZFkd994LP/8MycnCI04ikUgkkjaGyaTwyp8HeOy3vQzu4s+iewcTXk+3wiUdfXF30rHukPQtawpFUVi+J4uhXfzxdrOya6MhDh+GP/8Uaxhny3xbJBeWzgEepBVU2EfO/JZbwNFRdpe1UdILKgjxcsHJof7tbzsPZ56eGMWu1CJ+2Hai3mNKquo8y2z4jNJqRfLWAq6ICWZPevGp7jhV2blTFERKWiX55dX4W+hXBqeTZemFMpEqkdgLRVHYlJzH4M7t0FmY0LaIr77CwVDDV7ET2JZSIH4XFSUSZt9+K37OyoKSEvvNQSKRNMgv8WlM/mgT5dUGFtw1iLuHd0Zzzlqxd4QPeoOJgyfl+/RC0LqSZT17isphC6Qt1Eaj0RAT6k1SZit+Ad9wAxw9Km6wigLZ2c09I4lEIpFILgiVeiP3zt/JZxtSuHVQe76a3r/BwKmzg44hXfxZdzAHRam/U0EiSEgrIqOokon2kGD86CORJJk5U/2xJarSOcAdkwIn8u0QoPX3h6uvht83BLoAACAASURBVMRE9ceWtHjSCivqLWo4k2v6hDGsqz+vrThIZtH5HTUltnqWzZwJH3xg8WkTYoS8719JJ627bmNYmLiTXFzklelpZ6FfGUDYqWSZ7CyTSOxFSl45mcVVdvUrw2iETz/FOHIkGSHtWbX/jPuIpyf4+oqY3pQpwtt33z77zUUikZxFVY2RRxftZs6iPfRr78vyB4YxoKNfvcfGRfgAdpLllpxH60qWdewIs2dDYGCzTiMmzIsDWSWixbm1Ute99847EBMjZG1UpNpg5MO1RyitsoOZtUQikUgkVpBTUsWN87awan82z0yM4oVJ0TjoGl9Kje4RSGZxFYca8cGRwLLdWTjptIyNDlJ/8KefhkWLINgO8o4SVekcIHyHj+bYyfv3m2/g77/tM7akRZNWUEm4X/0SjHVoNBpeviYWkwJPL046r8ihpKoGJwctLo466ybx889w6JDFp0W2cyMmzIs/7SHFeOwYxMXBsmXqjy1pdqztLAvwcMbZQUtGPUljiUSiDpuS8wAYas9k2YoVcOIEulmzGN41gNX7s88v4NNo4KWXRGfZgAGwYIH95iNpcSiKwsIdafUWCUnsx/G8cq75eDML49OZPboL398xkADPhu/XYT6u+Hs4y2TZBaJ1Jcuys4UPgdEO0i0WEBPmjd5gso/nQkvjqqvAwwNGjYI1a1Qb9p9Duby56jALtqeqNqZEIpFIJNayP7OESR9tIjmnjM9v7c/tQzueJ49QHyO7iwKedQdz7T3FixaTSeHPvVkM7xZgm7xZQ9R1FElaPB39RTFWSl65fS7g4SGCQnq9fcaXtEiqDUayS6uIaKKzDCDCz41HxnXj74M5LNtzdnKqpNJg/WdUYSEUF1utgDIhJoSE1CL1g1nBwaKTYPNmdceVtAjySvW0c7e8s0yj0RDm6yplGCUSO/LvkTzCfV2J9Gv63mQ1Pj5CGWrSJMZGBZFVXEVSRj0qWMOHw65d0Lcv3HwzPPCAXCu1ERLSinj01z1c/eG/bD9W0NzTaRP8lZTFVR/8S1ZxJV//3yU8Mq57k1KsGo2GuAgfmSy7QLSuZNm330KvXlDZvBnx6FBvgPpvQq2Nrl1h0yax8bviCli4UJVhE2o/AH5PyFRlPIlEIpFIrGXtwWxu+FQEEn+551LGRJnf/RTs7UJUiBfrDkrfsobYmVrIyZIqruodou7ARqOQlVGxmEdiX9ydHQjxdrFfZxnAr79CUBCctIOknaRFkllUhaKIRJg5zBjSkd7h3jy3dB+F5aeDhSWVNXi5Olg3iePHxXcrk2VXxIrPxxVqSzG6ukLv3rBtm7rjSpqdCr2Byhoj7azoLAMI93WTMowSiZ0wGE1sSclnaBd/s4rvrGboUBGjc3RkdI9AtBpYfaABG5WQEFi7Fh56CFatgqoq+81L0mJISBWxV1cnHTd/vpUfttbv2yqxnRqjiReX7eeeH3bRKcCdZbOHMqqH+cp4fSJ9SMktp7hCKrDZm9aVLCuvrUJ1s2Nlhhl09HfHzUlHUkZxs87jghEaChs2wMCBwjz9hO0frgmphQAcyCrhsJSukkgkEkkz8fWmY9z5bTwdA9xZPGvIqYIYSxjdI5CdqYUXZGFbUK6nUt+8HfaWsmx3Js4OWi7rqbIE4/Ll8MsvUCCrJC8mOgd42FedITYWiorg++/td402QFWNkdu/2cH3F0FQJa1AdMdE+DYuw1iHTqvhlWt7UVxZw0t/Hjj1+5KqGus7y44dE9+tTJZ19HenZ4gXK/baQYpxwADYsQNMrdhCoA2SXyYSvdZ4lgGE+7o2nCwzGKydlkQiAfZmFFNaZbCvX9maNZB1+p7RzsOZfu19Wb2/gWQZCI/ft98WNiteXqIRQXYet2oSUgsJ83Fl2exhDOvqz1OLk3j8t73oDXJNoCb5ZdVMnbeVL/49xvRL27Pwnkub9NI9l97hwrdsd7rsLrM3rS9Z5uYG2ub9s3RaDdGhXm0nWQaivXvVKvjjD2jf3qahDEYTe9KLmdgrBJ1Ww+KEDJUmKZFIJBKJ+Xy49gjP/7GfMT2DWDjzUoK8XKwaZ1SPAIwmhQ1H7CvFaDCamPj+Rp78fa9dr6MmJpPCn0knGdU9EA9nKzs2GuK99yA8HK65Rt1xJXalc4A7Kbnl53tqqEW3bjB4MHz1lTC1l1jF83/sZ+3BnItinZ5WKyVnbmcZQFSoFzNHdGLRznT+PSJ8ZURnmZXJMpMJOneGDh2sOx+4IiaY+BOFnCxWudp/4EAoLYWDB9UdV9Ks5JVVA+BvZbIszMeVgnI9FfpzEmNLlojXcY7smJdIrKXOr2xw53b2uUBlJdx4o5BTPIOxUUEcyCo5VUTSIB7CQ5aXXoJhw+D11+WaqZWSmFZEXIQP3q6OfDH9Eu4b2ZkF21OZ+vlWckpld6FafLXpGAlpRbw/tQ/PT4rB2cFy/9teEd5oNEgpxgtA60uWubs39ywAIcW4P6sEo6kN3VBcXWH8ePHvZctg9myr/OMOZ5dRoTcyNiqIYV39WZKYiaktPY8SiUQiaXaqDUbmbUhhTM9APp3WDzcn6xM5cRG++Lo52l2Kcf2hXDKLq/hr30mqai6O7rKDJ0vJLa1mrAXSlmaxd6+Qkpk1S1TJSi4aOgV4UFptILe02n4Xuf12kRiQ0nNW8Ut8Ggu2p+Lv4cTejOIWX32cVlCJo05jccHD7NFd6eTvzuO/76FSb6SkyoCXi5X3guuvh+Rk8PW17nxgQq0U48p9KksxDhkCN92k7piSZudUZ5m7tTKMohMz48zuMqNRJH0zM+Hdd22eo0TSVvk3OY+oEC+rZVKbpE5Z4d57z/r12KhgANY0JMV4Lv/7H1x3nfh+zliSi5/c0mrSCyvpEyk6lnRaDY+O78GHN/dhf2YJV3+wid0yMaMKO44VEhvmzdW9Q60ew8vFkc4BHvL/5AIgk2V2IibMmwq9kWP2Mihv6WzfDh9+KDZeFhqD7qqVYOwT4cs1fcLIKKok/kShPWYpkUgkEkm9rD+US0mVgWmD2qNtwnC3KXRaDSO6BbD+cK5diz8WxqfhoNVQoTey/tDFUfG9NSUfgEFqV9Z+8IEo4rnrLnXHldidzgGimjnZnlKMU6YINYqvv7bfNVop+zNLeGpxEoM7t+O5q6PRG0zsy2zZahpphRWE+bg2aZ5+Li6OOl6+Npa0gkreWXOYksoavK3tLFOBLoEedAvy4E+1pRi7dIEFCyAqSt1xJc1KfnltZ5mn9Z5lwNlSjNu2Qd++4O8v9vqFco8ukVhKhd7ArhNFDO1qRwnGjz+G7t1h1Kizft3R350ugR7mJ8s8PeHnn0Xx2bx5cOiQHSYraS7qOpTiInzO+v3EXqH8eu9gdFoNN3y2hV93pjfH9FoN1QYjielF9G9vfcFUHXERPiSmFZmvwPHaa6KpRUptW0TrSpbNnAlvvdXcswAgJswLoMVvHu3GCy/Am2/CokXwxhsWnZqQWkQ7dyci/FwZGxWEm5OO3y8CiReJRCKRtB6WJGbg7+HEUJW8BEb1CKSgXG83jfHc0mrWHsxh+uAO+Lk7sXyvyp0HdmJrSj4Rfq6E+ZjnJWQ2l14KTz4J7ewkbyOxG50CROFbSq4dC848PeGzz+C+++x3jVZIcWUN987fiY+bI+9P7cMlHfwA2JXasitc0wsqLPaFqGNQp3ZMHRDJFxtTKKjQWy/DeNVV8Pzz1p17BhNiQth+vMA+0khSVq9VkXeqs8w6GcY6j7/0wjPk2vbvh5oaETQvLRUJM4lEYhE7jheiN5pU22Ocx86dIrF9332gOb9IZGxUENtSCiiuNNNLWaOBZ54BZ2eLY3uSlk1CaiEOWg0xYed7ckeFevHH7KH0i/TlkV9288If+zEYZcLFGpIyStAbTPSvXTfbQu8IH/LL9Q17ip7JP//A44/DypWwfr3N125LtK5k2ZAhcO21zT0LALoEeODsoG1bvmXn8sgjcPXV4oZaUGD2aQlphfSJ9EGj0eDm5MC4qCD+3JtFtcFMSamCAnj6aSEPIZFIJBKJhZRU1bDmQA4Te4XioFNnqTS8awBaDaw7ZIZvWXIynLQs2bU4IQODSWHqgAgujw7i7wPZLV6K0WRS2H68gEEd7ZDQmjFDJMskFx3BXi64Oek4as/OMoBp06B3b/teoxVhMik8snA3GYWVfHxLX/w9nAnyciHMx/WUKkRLJa2wkgg/6xPyj03ogb+HM4oiJHAsRlGELGyR7UnFK3uFoCiwcp+ZXQHm8vLLEBoKFU342EguGvLL9Hg4O+DiaLkvCoC/hzNOOu3ZAbkDB0TX9lVXia933xXeSBKJxGxW7juJk057quBEdbZsAS8vmD693ofH9AzCYFIsU6EIDIT58+G559SZo6RFkJhWRM8QrwbvE37uTnx3xwBmDOnAV5uOcdtX2ykst0w5TALxx0U8vH8H2zvL+tR2ASaYI8WYlgYxMUIC/IsvbL52W6J1Jct27hTVTi0AB52WHiFeJGWUNPdUmpeXXhJVZ8uXm3V4UYWelNxy+kSe/hCZ3CeM4soa1psTYAQRHHvxRVFVvm+fNbOWSCQSSRvmr6ST6A0mJsVZryl+Lr7uTvSJ9G3at2zrVoiNtaj6S1EUFsan0TfShy6BnkyICamVYjTzvtlMHMoupaiihkGdVEyW1dSIzUCZnRMtEruh1WroFOBu386yOrZvh1dftf91WgGfbUhhzYFsnryyJ/3anw7w9Yn0IcFSuXRzpWNUoLzaQEG53urOMgBvV0demBQDgL+HFV06mzaJJFTHjlbPoY6ugR50DnBnhdpSjDExwo9q1y51x5U0G3ll1bSz5vVai1arIczX9exk2f79QtpNp4NXXhF7fFeVO8MlklZMRlEli+LTua5fOK5O1iWym+T++0WQ3Pv8biEQwXZ/D2dW7bew6OLaayE8XIUJSloCRpPC7rSiU35lDeGo0/LsVdG8cX0v4o8XcvVH/3Igq43HuS1kx/FCOvq746+CR2H3YE+cHbTm+ZZNmwYJCeJ7To6UYrSA1pUsu+suYTzZQogJ9SIps9h8LdHWSEwMpKTArbeadXidZu6ZH9hDu/jj7+HEkkQzpRivuw4efFB4pQ0dKlpPJRKJRCIxk8UJGXRo53aefrutjO4RyN6MYnJKGpDPOnAArrwSwsLO8xhojMS0Io7klDGlfwQAl3Zuh4+bIyuSVA6mqkydX9nATipW1i5eLNaD69apN6bkgtPJ38P+nWUAq1YJeZJjx+x/rYuYzUfzeGPlQSb2CuH/Bnc467G+kb5kFldxsthMWcCNG2HQIIiPV3+i9VAX6I/wsz5ZBjA+Jphf772UqywxZjcaYeRIGDZMSH+OGWPTHAA0Gg1XxIawNSWf/LJqm8c7xcCB4vu2beqNKWlW8surrZZgrCPc15X0onM6y+q87aKjxXtZIpGYzYdrjwAwe3QX+1ygrjvYy6vBQ7RaDWN6BvLPoVzz1Zvq2L1bdJVaoBwlaZkk55RRrjeavd+9oX8EP88chN5g4tqPN6vvn9pKURSFnScKVPErA5G8jA3zPhU7r5clS0QnqKKI4pa334Y1a0DbulJA9qR1PVPl5eDu3tyzOEVsmDelVQbSCtq4NEH79uK7GTr4u1KL0GqgV/jpD2wHnZaJvUJZcyCHkiozdJXHjBGSEFu2QHCw0FduywlLiUQikZjNyeIqtqTkMykuDE09Ov+2MKp7IADrD9fT8ZWWBuPGgZOTCOD7+oqFrRlyjAvj03B11DGxNojrqNNyeVQwfx/IadFSjNtSCgj3dbWp4+M83nsPOncWSUfJRUvnAA8yiirt//qdPl14cXzzjX2v01IpKhLKHI2s0U8WV/HAggQ6BXjw2nW9zvtc7Fu7+W9SivHoUbj+ehg+HDIyID8fCgvtLpueViACh3X+S7bQr71f05J22dnw7bfi3zqdSCa8+674jK9LMtjIhJgQTAqWdwU0RlCQ2LPJZFmrIb9MTzsbq9jDfV3JqPMsUxThgXTjjacPqKoSBSqff27TdSSStsCJ/HIWxqczdUAEoWp79YLoGunbFx59tMlDx0YFUVZtYFuKhUkvrRaWLYOPP7ZykpKWQmKaWLdZUhzaJ9KXP+4fSs8QT+6bv4s3Vh7EZJKx1sY4mltOYUWNqrKrvSN8SMoopqY+D7msLLj9drH2NNbuoxwcxPeCAhkbNxOZLLMjdSaJe9uyb1kd8+dDRAQcOdLoYQmphXQL8sTD2eGs30/uE4beYOKvvY0EDVetgjlzxOsAoEMHIXuyaJEIhFRXyw8GiUQikTTKH7szURRx31GbniGeBHu5nC/FWF4uEmUlJfDXX9CpE6Smio6Xxx5rdMwKvYE/dmdxZa+Qs+6dV/QKoazawIb6EnMtAJNJYduxfHUlGHfuFPf9+++XlXMXOZ0C3FEUOJZnZynGiAgYO1YkNy4iaZKyagNHc8vYfDSPxQkZzNtwlH+P5J1/oKJAbq6oBK9j7lyRwPH3F0n5/v3Fz/WskWuMJmb9uIsKvZFPp/XF/Zz1OUBUiBfODlp2NSbF+Mwz0LOn+HybOxcOHxbds1FRTX7G2UpabaDf1s6yJtmxA267DSIjhWfi8ePi96++KhQvGpDDsoaeIZ50aOemflX3gAFCmlTSKsgr01snG3oG4b5u5JXpqdQbxX760UeFJ3kdzs5CmvHFF4UMskQiaZD3/j6Cg1bDrFF26ir7+284dMgsP9YhXfxxddSx2tKii9hYUZD23nvS4/IiJyG1CG9XRzr6WxZDD/RyYcHdg7ixfwQfrTvKnd/Fi3uEpF7q/Mr6qeBXVkdchA/VBhMHs0rPfkBRRKKsshJ++OF0kgxg5UrRTLJzp2rzaM2cv+NRAY1G4wIsAiKAPcBtyjlahBqN5hLgd+B47a/uAE40dV6jlJeDh4et01eNrkEeOOo0JGUWc2WvkOaeTvMyZox4oz79NPz0U72HmEwKiWlFTOx1vrxJ73BvOvq7szgxgymXRJx/ssEADz0kpBdfeun07/1qs/c1NTBxotiUv/22qPSUSCQSieQcFidmnLrnqI1Go2FUjwD+2J1FjdGEo642oePmJha2Awac3uB26QIPPywCrTNnCh/Oelix9yRl1YZTEox1DK6VYvxzbxbjooNV/1ts5UhOGYUVNQzsqKIE43vviXXgjBnqjSlpFjoHiPX80dwyeoY0LCWkCjNmwNSpQrrzssvse60mqNQbyS6pEl+l1eSUVJFTWn3qdzkl4t/lZwQlXGqqaFdRQoZ3INf2DePFyiTcli+F5GTxVVoq3hclJSLYXVIifr7+etGF2bGjkGvSaMR6+corhS/JtGm8si6VnScK+WBqH7oEetY7ZycHIQdzXmdZTY1Y+2s04OIiEklz50LIGXuim26CDz8UgfbISHs8paQVVOLqqLNZjq5BDh4Ur6GtW8XzOnMmzJolivbshEajYUJsCPM2pFBYrsdXrb/t3nth0iQRbFG5s1pyYTGZFArKq2nnbltnWVht90tGUQVdTOWiSj009PTrQ6MRfuFXXikCc/L+K5HUS3JOGYsTMrhjaEcCvVzsc5GPPxaFMNdf3+ShLo46hnX1Z82BbF6YFG2Zmsbjjwu7ky+/hNmzbZiwpDlJTCsiLsLHKiUVZwcdr14XS1SoF88u3cf8bSe4c1gnO8zy4mfH8UL83J3opGJsoa4bMDGtkNjwM4qxPv5YFKZ99JHwFz2TgQPFuvzLL0WhnKRR7FV2Ow1IVxSlN+ALjK3nGF/gE0VRhtZ+HTLzvIZpYZ1lzg46ugV5kiQ7y4S0x0MPwc8/C4PBekjJK6O0ykDfegwmNRoNk+JC2ZKSX78nwhdfiKq2118XElbnotNBr17w/vswZYrItEskEolEcgbJOaXsyyxhUpz6XWV1jOweSFm1gR3HC0Qw+cgREWyaMwdGjDj74CefFP5ls2efllE4h4XxaXRo58Yl51SrOeq0jIsKYk0LlWKs8ytTrbPMZIL0dBGoU7GDQ9I8dPR3R6OBlFw7d5YBTJ4M3bqZJXlqL8qqDUz/ajs9n/mLMa+t4YG3lvHZu4v458P5FH72FV1/+Byn8jJ6hnoxt3wP25Y+yb7v7+Xo+1M4+Pb1bPr0duYMCGRJYiY/fLea8u07RfXo9OlChuWnn053jr3xhvAt+PRT8blz/fWisxWEPGJuLtx7LzUhoUQ8/xhzIo1N+nT1be9LUkaJ8D5RFOGVEB0Nv/4qDnj8cbFWDzmnePChh8T3d99V8dk8m7TCCiL8XNWV1T158vR+JiREFOu9/754/t5///wAhR24MjYEo0mxvCugMUaNgltukYmyVkBRZQ0mBRU6y0SyLK2wUhSkdOggilTPZMIE6NMHXnmlwbWKRNLWee/vI7g46rhnRGf7XCAtDZYuhTvvFB2fZjA2Kois4iqSMkosu9aQISJZ9uabsqP0IqWs2sCh7FL61BN7NReNRsP0wR3oE+nDgu2pWNLn0pao8ytTcx0a7uuKv4cTiWln5BqyssS6fvx4Ufx0Lj4+Ys3/44+yK9QM7JUsGw2srv33WqA+l3pf4DqNRrNdo9H8qhGvHHPOqx9Fgd9+g2nTrJ+1HYgJ9WZfZon84AD473+F3MuTT9b78K5UYVDYJ7L+9tTJcWEoCizdnXH2A8XFQt5l+HAR8KgPrRbeegveeQd+/110uuXVI1cjkUgkkjbL4oRMdFpNk4FhWxjaxR8nnZZ1+0+KxM6AAQ37BXl4iMD2zp2iCuwcjueVs+1YATf0j6h3AX5FrJBi3FifPFszszUlnzAfV/Wk0bRaWLtW3OslFz2uTjpCvV05mltm/4u5uIjuoFtusX4MRTkdQF67ViRsfXzEutfXVygdrF0rHl+2DAIDRSFZcDCm4BD0gcEUb9jMfSM787PTQbZ9/H8s/+ZBvl/4DG8sfZP7l3/Cd2ND+Ojmvlw7sANBkcG4jx6B7t57RPfpl18ya2wPlswawm9X3UH0Te/z0PSXKXrtLSEBeOWV5kmTdugAu3aRvmw1f3Xoz7TdfzFr1iQhMdgIfSN90BtNpKzcCKNHi/W4g8NphYeGAgSRkaKrb9484aNgB9IKKtTzRdy1C269Vcz7jjvE77y9xWf07NmiQ+8CER3qRYSfK38mqSzFuHt3k//fkpZPflk1gAqeZeK9k1FYCQcOiMICR8ezD6rrLjtyRNgfSCSSszh4soQ/dmcyY0gHm9+TDTJvnliLzJxp9imX9QxCq4HV+60oFnruOSF7LhPkFyV70otQFMv8yhpi6oBIjuaWs+N4E961bZCc0iqO51eo6lcGIlEZF+FzyncOEMVbP/wAX33V8Lr7zjuFwoS8VzeJXWQYgXZAXYqzBKivvC4ZeFpRlOUajWYzMMLM8+pHoxEyey2MmDAvfo5PI6u4yj4mnhcTPj6isvSZZ+DECWEifQYJqYV4uTg02J7awd+duAgffk/I5O7hZ1TkvPKKSHy9/XbTlZD/+Y/wp7jlFtFhVhe4kEgkEkmbRlEUFidmMKSLPwGedtrIAu7ODgzs6EuPN5+HDYvg5ZdF4LwhbroJNm4UHgHnsGhnOloNXNc3vN5Th3Txx9tVSDGOjQpS60+wGUVR2HasgJHdA9QZsLpaLPwDAs4P4kkuWjoHelyYZBmI9aPJBNnZ53c/NYainPbhuvpq4b8VGioS4XWFcooivurGDQuD664DRaFSb2DdgWzKqmr4742DGDq+B3QAIn3E58KZX3WJmClTxFc9xHjC0vuH8tG6ZD5al8zGI3m8dE0Ml1sgxVquN/J/hxwpnPI4A6d2J/CvpdCvn3jw1VdFF9Vdd531PPWN9GXOP9/S4/VF0K6dkIG5666zvRIaYs4c+P57WLHCtoRlPSiKQkZhpTpyr+npQg7X2VlU7M6aZfuYNqDRaLgiJoSvNh2juKIGbzeVPvtmzBD/h6tXN32spMWSV6YHoJ2NnWWBns446jSkF1YKFZdeveo/8Jpr4KmnRAGQRCI5i3dWH8bT2YG77ClT98ADYq9ggQSwn7sT/dv7sfpADg+Ps7Aj+rLLml26WmI9CbWNCmokyyb2CmHuH/tZsD2VAWrK67cCdtYmENX0K6ujd7gPaw7kUFxZg3d5sZBgvfbaxk8aNgy6dhVqD7fdpvqcWhP2SpblAXUaON61P5/LcSDpjH8HmnkeGo3mbuBugMg6ffvycmFo2a+f2IS2EKLDxJ+TlFEsk2Ugqk+mToXw8wN7CalFxEX6otU2nPCaHBfKc3/s59DJUroH13onTJ8uAhN1G/mmuO46IU3TgvztJBKJRNK87DxRSHphJQ+P7Wb3az0Q/xuXbFhE6cz78HzsscYP1mhE4PkcjCaFRTvTGdk9kGDv+r0P6qQY/0o6SbXBiLNDy/DrPJJTRkG5Xj0Jxp9/hrvvFt0d0dHqjClpdjoHuLPjWAGVeiOuThfgtXvVVaL4atu2po9VFPjjD5Eki48XnUZ1+48ePRqXFezTBz75hPTCCqZ9sY2c8Go+v60/Q7r4nz6/Rw+r/wwnBy0Pje3GuOgg5vyyh5nf7+Tq3qE8d3U0fk14WymKwmO/7SUlt4wf7hhIYBd/sXavY/duIek4d67YkE+fDpddRqCXC9kdu7Pa/zbG/fCeZVKosbGQkiK801SmuLKG0mqDOh2sa9aIROH27ae9JZuZCbEhfLYhhTUHsrmuX/1FExYzcCAsWCCSx+Z0I0paJHm1nWX+NnaxaLUawnxcOZlTBEePigKe+g8UnwsSieQs9qYXs3JfNv8Z0xUfNzt5Z4IoGGugkKYxxkYF8dKfB0grqLD8XmkwiPtFRASMHGnxtSXNR2JaEZ383VV5Tbo5OTC5Txg/x6fx7FVR9n2dX2TEnyjE2UFLTKj6FgFxtRKax5auIu72KUL6fPz4xk/SaESirAXlTFoq9loB/w3Uit8zGlhXzzEPAzdpNBotEINInJlzEq+UbQAAIABJREFUHoqizFMUpb+iKP0DAmqrktPThSHx+vVq/Q2q0DPYC60GkjIt1AFurbi6ikSZopwlt3JKM7eJyoaJvUPRaTUsTjxDirFnT1FJYwlDhpze6D7xBCxfbtn5EolEImlVLE7MwMVRyzgLOjCsYvlyLvnsDRZHjeC3aY+Y7w1TVCSC1rt3A7DhSC4nS6qY0r/xAOkVsSGUVhv4twVJMW6r8yvrqEKyTFGEj0qnThAVZft4khbDhJgQKmuM/Lwj9cJccMwYkQjZt6/pY2fNEvuOggKx6TxyRMjzmcnR3DJu+HQLBeV6vr9j4OlEmYpEh3qz5P4hPDy2GyuSshj3zj/81YRk37ebj/PH7kz+e3l3Btc3pwUL4PBhse5etUrIO77/PgCFV13Ls4Nvtc4zsC5RVl1t+bmNkFYgPIpVkWF0dhYSkw111jQDvcO9CfNx5c+9KkoxDhggJO4PH1ZvTMkF55QMYxMJcnMI83XFdPiISKD27Nn4wfHx8MgjpztrJZI2zturD+Hj5sjtQ9UvCDnFAw8IiWcrGFOrPLHmgJX+l888I+Jp8j1/0aAoimhUUKGrrI6pAyLRG0z8tiuj6YPbEPHHC4iL8MHJQf3US69wH9z0lXR86F6hQDF4sHknDh8One3kndiKsFeybD4QptFo9gAFwFGNRvPmOcd8CMwAtgG/K4qyv57z/jb7iuW1BuDu9Uv4NReuTjq6BnqyL6O46YPbEnfdBSNGnNI43pMmNHP7tm+8PdXfw5lhXf1ZmpiJaeO/wqAw2wZj64oKsdm/+mqh8yyRSCSSNkeN0cTyPVmMjQrGw9leTfe1jBkDr7/OR7c+yTpLEliKIjqoZs8GReGX+DT83J0Y3aNxecUhXfzxcnFgubnB1Ib801Rka0oBod4uRPip0HG/aZPwEXrgAfMTj5KLggEd/ejf3pfPNx6jxmiy/wWnTROygV9/ff5jRqN4/6WliZ+nT4dvv4VDh4R3lZP5Aen9mSVM+XQLNUYTP919Kf2aWPvagqNOywOXdWXp/UMJ9nbhnh92cf+Pu04F0s9k54lCXlx+gDE9g7hneCOb6K5dhTdgRoZIntVWk/eN9CGruIqs4krrJjt3rihkU9H/JK1QGJir8lkzdapQMWlBnzMajYYJMcFsPJJHSVWNOoMOHCi+m9NhKWmx5Jfr0WpQpcI/3MeNJMVdyKUOH974wbt2CWuENWtsvq5EcrGz80Qh6w7lcvfwTni52EkmPCkJPvhAeApaQUd/d7oEerB6vxUxNQcH+O9/YcsW+Pdfq64vufBkFFWSV1ZNn0j1kmVRoV7ERfjw4/ZUFJk4BaBCbyAps4T+dpBgBPB2deSNzd/geTIdvvvOMt/c7duFDGONSmvHVohdkmWKolQrijJRUZReiqLcqijKMUVR/nvOMVmKooxUFOUSRVGebeA8899lLTRZBhAd5kVSpkyWncXYseLGvmABAAlptZq54U1/YF/TJ4zMwnIqZj8ImzfbJqfo5ia6ES+/XJihPvWUrIqRSCSSNsaGw7kUVtQwOS7UfhfZsQPy80V3wpw5DI0OZcvRfCr1ZgaGfX2Fv9nGjZR98wOr92dzTZ+wJivVnBy0jI0KZvX+bKoNTVxrzRrhdfDdd+bNyQqEX1k+Azu1Q6NG0Pn994UnqgVdPZKLh/tGdSajqJIliZn2v1hAgJBi/P7705tHg0H8HB0t5Me+/FL8fuBAsck0x5PrDHaeKOSmeVtwdtCycOalRIVasLG1gZ4hXvx+3xDmXN6dlftOMu6dDSzfczqBnldWzaz5uwj1ceWtKb0blUQ/hZubeE4uuQSAPpEiGLDrRJF1k4yOFsnH336z7vx6SCuoS5bZ2FlWWdliAwoTYkPQG02sPaBSoUOPHiLgIpNlFzV5ZXr83J3QmfNeboJwX1dSTM5U3Ti1aemm6dPFMS+9ZPN1JZKLnXdWH6aduxPTL+1gv4t88onYW8yYYfUQY6OC2HasgOIKK+5zM2aI9dOrr1p9fcmFJbEu9hqhbhLn5gGRJOeUEX+i0LwTMjPhwQeFBHorJDGtCKNJoX8HO/m4LV3KlduW893QKShDh1p2bk6O2N9Y2ZHaFmg9QuQtOFkWE+pNdkk1OaVVzT2VlsMNN0BcnGjb1uvZdaKQzgHuZplTj40K4vrD/+Kxe5cIHNr6f+7hAUuXwp13ioX9//2fqlWtEolEImnZ/J6Qga+bI8O7BdjnArt3iyKRu+469avRPQKpNpjYkmLBBuH226FfPzSPzsGxsoIp/SPMOu3KXsGUVhnYlFzPtUwmscHNz4e+fWHQIBHseuwx8ZjKHM0tI69Mz6BOKmwc8vNhyRLxvLbA9Z/EdkZ1D6RHsCef/nMUk+kCFDPNmCE2kCtWiKRxjx4iKebsDAsXinWrlWxKzuPWL7fh5+7EL/cOplPAhfXOddRpmTWqC8tmDyPM15VZP+7ivvk7ySmp4oEFCRRW6PlkWl+8Xa2rfo8K8cLZQcuuVDODJOcyaZLoWnvtNdUK19IKK/B2dbS9ov+770TBQkbLkxfqE+FDsJeLelKMWq3ooHv5ZXXGkzQL+WXVNvuV1RHu58rA1L3k/ru96YNrC4L45x/ZaSJp02xNyeff5DzuHdkZd3upVpSWivvTjTeCv/VyzmOjgjCaFNYftqLows1NJDz+/POUVLykZZOQWoSzg5YeIZ6qjjuxdwiezg4s2NaIfLqiQFbtesXXVxQ9zpmj6jxaCvHHC9FooG+knRQkDhwgv0csLw28ifRCC1Udxo+H0NDTRYCS85DJsgtATJjQ7t+XIX3LTqHVwiuvwLFjKPPmkZBWdKoitSncjDU8sfE7DgR3ofrmW9SZj4ODkGF8802xWZeG1hKJRNImKKs2sOZANhN7heKos8Nnf0qKWJB6egpvrVoGdPTDzUnH2oMWbEx1OpQPPsA9L5sXkhbTPdi8Tc7QLgF4ujiwfM/Jsx8wGkVX9eOPw48/gp8frFwJd98tAtbXXgtlZebPzwy2pAi/0kGdVPAra9cO9u6Fhx+2fSxJi0Sj0XDvyM4k55SxyhqJIEuZMEFUWV5xBaxdK/y3fv8dEhJEoZeV68PV+7OZ8fUOIv3cWHjPpYT5qCALaCXdgz357d7BPDq+O2v25zD0tXVsPprPi5NjiLbBgNzJQUtsmLf1yTKdTgRMdu6EdfXaVltMWkGlOhKM69aJDtZQO3YfW4lWq2F8TDDrD+dSVm1QZ9D+/cXfK7loyS/X087DdglGEJ5/z635DLe5z5l3wl13iU4T2V0maaMoisLbqw4T6OnMtEHt7XehH34Q6/T77rNpmLhwH/w9nK1fZ913nyi2K5ZqWhcDiWlFxIZ5q77vdXNyYHKfMJbtzaKoQn/2g4oiCnFGjIB+/UTHvqurKM785ptWWVyx43gB3YM8rS5Ca5L//Y+s5X9To3M81S1oNg4OoklkxYoWWQjWEmg9GYERI8SmtkuX5p7JedRJrCRJ37KzufxyGDGCms/mUWCJZu777+Obf5LnR93O+iP56s1HoxGGxNde26L8CCQSiURiP1YmnaSqxsTkPnYIgmZni3udXi+SUBGnO8GcHXQM6eLPuoO5Fmm7J0VE8fTYe3C8Z6bZ5wgpxiBW7z+J3lDbLWYwiC6aL76Ap5+G++8Xv3d0hE8/FYm9P/4QPk0qsjUln2AvFyJtlUWre866dYPgYNsnJmmxXBkbQqSfG5+sT7a/D4KDA1x5pfj+0UcQHw+TJ9tURLUkMYN7fthJVKgXP909iEBPFxUnbB0OOi33jezC8geG0q+9L3cN68gNZnaqNkbf9r7syyhpWvK1IW69FYKCRPGaCqQVVhDuo8Jnzdq1MHp0i90fXBEbgt5gsqz4ojFycuCFF2D/fnXGk1xw8suqaeeuTmdZmIcjnQrSyQ7taN4Jbm7w7LNw6aV26VCXSFo6/ybnsf14AfeP7oKLo85+F/L3F36aAwbYNIxWq2FMz0D+OZRr3f3b11f4ljXlaShpdvQGE3szilX1KzuTqQMi0RtM/LarNgGjKLBqFQwbJny7U1LgiSdOr6ufegoiI+Hee1us3LU1GE0KCalF9vEr++mnU0Vl3du3w8lBy25Lk2UgFGtMJpGslJxH60mW+fvDqFEtsrPMw9mBTv7u0rfsXDQa+PZbVn72K2g05ren3nEHxk8+ITmqP0sS7ZAFN5ng+edFkEQikUgkrZrFiRlE+LnaRyJh1iyhx75sGURFnffw6B6BZBRVciTH/O6tn+NTWTjgakZdMUhsQMxMHlwZG0JJnRRjTQ3ccovQKp87VwRFzwwCazTwwAOwa5dYSANUVJg9x4ZQFIVtKQUM6uRnu1/Zs8/CddeJpJ+kVeOg0zJzRCd2pxez+aiKRVJN4e5uc3Jk/rYT/OfnRAZ08OOHOwfi46ZOp4dadA3yZMHdg3jyyvM/n6yhb6QPeqOJfZlWqmm4uIgu13nzbJ6LoihkFKrQWbZvH+TmimRZC6Vfe18CPJ1ZoZYUo9EoPmNXrTL/nBMnYP58mD1b+Nh17QqbNqkzH4nF5Jep11kWlJ+Fs9HAsSALOmRmzRKytVKtRdLGUBSFt1YdJtTbhRsvsb0IpVFuuEHcM1Uo5BgbFURZtYGttQoQVlFSAqtX2zwXif04eLIEvcGkul9ZHVGhXvSO8GHB9lRR4LZ5sygcPXFCxFeTk0WBpnNtMYe7u5BiTEqCDz6wy5yag4MnSyirNnCJ2n5lycnCPujll0FRcNRpiQn1sryzDKBzZyE172cnT7WLnNazetmzBxYsaLFeU9Fh3iRJGcbzad+e+NxqPB2gm6cZVTeKAv7+6O65h4m9QllzIIeSKpUrELRa2LpVVNoXWWlSLpFIJJIWT05pFZuS85jUO8z25E19fPghLF8uqqvrYWR34ZFmbjdAVY2RJYmZXBEbgldZseiAMdOYd2hXfzydHVi+NwsKC4XU2RtviIq+hujdW2zADx0SC+offzTrWg1xNLecvLJq2yUYS0pOb6gc7OQDIWlRXNc3nABPZz5en9zcUzGbT/85ypO/JzG6eyBfz7gED3t5lrQg6ooOdplr7l4fo0dDeLjNc8ktrabaYCLC1i7WOknIUaNsnpO90Gk1TIgJZt2hHCr0KhQQhISITuht2+p/vLhYBERfeun03vv112HaNPj6a+EHbTKJQgzJBaeqxkhptUE1zzLdwQMAHPCx8H1pMsGiRWINIZG0EdYezCExrYgHLuuKs4Mdu8pWr1ZVKn1IF39cHXWssUXy+okn4KqrhLKGpEWSkCrim3F26ixDUXjYkMzAlQvZeaIQBg8WKiXJyUKu06UedYWrrxb70XHj7DOnZiD+uFgH91czWWYwCAUGR0ex1qqNXcRF+LI3o5gaoxWd3N9+K7r6JOfRepJlv/0GN9/c3LNokJhQLzKKKiks1zd9cBsjKTmbv76chW5uExuqPXtEwPHwYQAm9wlDbzDx196TjZ9nDa+8IoKJr72m/tgSiUQiaREs252FSUF9Ccb9+8WCNjgYRo5s8LAQb1d6hnixzsxk2cp9JymtMnBD/3DhpXT8OPznP1BV1eS5zg46JnTxYc3eDPR+/sKE+7//Ne/vadcOuncX3WhPP221rNK2Y6IraKCtybLPPhPFLI89Zts4kosGF0cddw7tyKbkfOukRi4giqLw5spDvLriIFf1DuXTW/vZV4apBRHo5UKYj+upYIzVHDgggibHjlk9RFqh6IaN8LUxWTZypCgsaG9H3xkVmBATQlWNifWHctUZcODAs5Nl8fFwxx0QHS0kt8aNE8GtI0fE4w8+KO4rxcUiwbhpEyxcKB6zt3yq5Czya+MN7dxV6mStleNMcAuy7LyiIuGJMneuOvOQSFo4iqLw9urDRPq5cV0/24s+GuTkSVEw99xzqg3p4qhjeDd/1hzItl7y+sEHhfT8GR7NkpZFYloRgZ7OhHqrLAmuKKJAdOBARvzn//i/hGUs2HpMJHSmTDndSVYfGo24T8TEqDunZmTH8QJCvF3U9Sh+9VXR1PHxx2cVlcVF+lBtMHHoZKl14+r1sH27SpNsPbSeZFl5uchS61rmZjQ2TBhmWy1L0kqp1BvZnV9NUVQv0X7bkLmgogg/sSNHhGEw0Dvcm47+7vyeYAcpxrg4kXx97z0hoSWRSCSSVsfixAxiwrzoEuip3qD5+SK4OtM8T7HRPQKIP1FIcWXTXdIL49OI8HNlUMd2oqrs/feF9vtbbzV9oYoK/vfJozz1+9tsTs61TLba31/Icd1xB7z4otj0lJebf34tW1MKCPJypkM7G4LXVVXw9ttw2WVC6kvSZrhlUHu8XBxadHeZyaTw/B/7+XBdMlMHRPDujXGqG6i3dPq292VXqg2dZQCenrB+PbzzjtVDpBVUAtguwxgba35hQTMyoKMf7dyd+FMtKcYBA0Sycvly8XNuLixZAh07io6xVatEYWGPHuLxbt2gV6/Te/HgYFHUUVEhJJhU9r+UNEx+WTUA7VTqLGPmTD5+4WuOVFn4WebnJyrWFywQXQWSC0K1wcibKw9RIIu0Lzgr951kX2YJD17W1b73/i+/FJLqd9+t6rBjegaRVVxlvSJW165w/fVCbq9YWtC0RBJSC4mL8FFXUWXHDrFmmDhRrBU+/5zvP/qdZUk5FFdYoAJWWChisJZIQLdAFEUh/nihul1le/YIq6CpU8XXGfSJEF2CVkkxgugIHT5cPP+SU7Se3Vt5eYv0K6sjOlQky6Rv2dkkZRZjMCkUPvqUkPFoqPLszz9hzRqhn+8rJF40Gg2T4kLZeiyfrOJK9Sc3d67oDHj+efXHlkgkLYa8smpmzd9FdknT3TmS1kNKbhl70ouZHBem7sBz5ojF5oMPmnX4qO6BGE0KG4803g2QVlDBpuR8bugXgVZbu8EZM0b4dr30EqSmNnxyWRlccQV+WzeS0Kk3fyZZ0ZHt5ASffy4SVb/9JiS3LEBRFLam5DOwYzvbNmjffy8qamVXWZvDw9mB6YM7sHJfNsk5VlZP2omTxVV8t+U4Uz7bwjebj3PXsI68fE0sOq0d5F1bOH0jfcgqrrJtbR4eLjpZv/gC8vKsGiKtQHSWhdvSWZaaCitXmtW929zotBoujwlm7cEcqmpUsCW47jrRPVYndTtunAiCLVsmOsrGjgUfM2ScDAbx/N18s5ANktid/LLazjKVPMvw86Pm0iHklFZb/tp6+GFR3CPVWi4Y6w/l8uG6ZH7a0ci6UKI6RpPoKusc4M7kPirvLc7EYBAKC2PHiiIFFbmsZxBaDazeb4Ny02OPCbn0zz5Tb2ISVSgs13M8v4I+avt0u7qKve+XXwoVsDvvZMqQzlQbTPyWkG7ZODt2CE+z6mp153gBySiq5GRJFZd0UPF5jo4Wfr4ffXTeQ+G+rrRzd7I+WTZtmni+58+3cZKtC5ksu0B4uzkS4efK3gyZLDuThNrK0x5DeovKmC++OC3nUUdNjajo7NbtPD3VyXFhKAosTbRD91enTsITReWKHYlE0rL4aXsqy/dmsWinBYs5yUXP4sRMNBq4qreKEoxr14pg4Jw5osLeDPpE+uLj5si6g40nyxbtTEejgevPlXWp6yprqNikuFhU9f/7L5r58ymfOo1V+7Ot0zXXaOChh4TE1uOPi9+Z6RV7LK+c3FIV/MomTxb35ssus20cyUXJjCEdcXXU8cn6lOaeCsfzyvnsn6Nc8/EmBr3yN88s2UdxZQ0vTIrmiSt62scH8SLgtG+ZjVKMc+ZAZWW9gQFzSCusIMDT2TYJzIULYfz4i6ba9oqYECr0RnWkGDt1EonCyy8XP+t0p/wxLMLLC/76SxR33H77ab9Jid3Iq+0sC1Cjs0xR4JVXiM4VkqiZRRYmwUNC4M47hS9KWprt85E0yYbD4v3/9wHzJL4l6rBsTyaHs8v4z5hu9i2UWb5cvJfuu0/1of3cnejf3o/Vtrx2+vYVxRW7d6s3MYkqJKbX+pVFqOxXFhMjkmS33y6KIxDNIr3DvVmwPdV8WU8XF7HmO3JEyF9fpNT5lfVrr1KyzGQSa7AZM041jpyJRqOhd4SP9cmyuDjxvv38cymbfQYyWXYBiQn1Zp9Mlp1FQmoRkX5uwoD4qaeElu28eWcf9N13cPCg+MCs/fCto4O/O3ERPiy2R7IMhIxWv372GVsikTQ7iqKcSpL9ZU23jeSiRFEUliRmMLhzO4K8VNJsr6wU94zOnYWvl5notBqGdw3gn8M5mEz1L1CNJvE6HdY1gNBztc/btxfSWG++ef6JigLXXCOq9BYuhKlTuSI2hKKKGjYfzbfkrzubESPEhqawEPr3P+1L0whbUwoAGNTJRkmKgABRcdhGExFtHT93J24aEMGSxAzSaz2pLhSKonDwZAnvrjnM+Hc3MPLN9byy4iAGo8Kcy7uz5uERrH54BLdd2qHNJsoAeoZ44eygtV2KMSoKrrpKJFcqLP+/TiuoJNzXRgnGtWuFzGBIiG3jXCAGdfLD182RFUkqSTGqhZsbLF0KkybBAw/Ahx8294xaNac8y9ToLEtLgyeeoPPRvYComLeYRx8Va6PGOuAlqqAoChuO5KLRwK7UwlOSnBL7YjCaeG/NEXoEe3JlrJ3vFxs3QmSkkLyzA2OjgjiQVXKqO9sqFi+WXSotkITUIrQa6BXurc6AJ06IYojUVNCen1qYOiCSw9lllq0Hx42DG24Qqik2+NY2hdW+fGYQf6IAD2cHegR72T5YUZFIRi5d2uhhcRE+HM0to6TKAtnLM7nzTiH1uHOndee3QlpPsuytt+CXX5p7Fo0SE+bN8fwK61/ArQxFUdiVWkifyNrKhuBg2LxZGBeeybRp8OOPYsNcD5PjQjmQVWK9oWFT5OaKLP6OHfYZXyKRNBs7TxRyPL+CqBAv9mYUX/Dgq6R5SEwr4kR+BZPUlGDMyhIFH599JmQkLGB0j0DyyvQNdp9vPppHRlElU/o3YBY+dqzwhjEYxFcdGo1I3P36K1x7LQDDuwXg4ezAn3tUCKYajaJQ6cYbhWRxIxuPbcfyCfB0pqO/lYVNiiI80/7+28rJSloLdw3rhEYDn2+wf3eZyaSQmFbEKysOMOrN9Yx/dyPv/X0ELxdHnp4Yxb//G8Ufs4cya1QXugR62H0+FwNODlp6hXvbniwDePJJ+N//rDo1vaiCCFskGGtqYMMGGD3a+jEuMA46LZdHB/P3AZWkGNXE2Vns1WfNkp3Bdia/rBpXRx1uTg62D7Z/PwAefUS3fHqhFcmyyEgxzpAhts9H0ijH8ytIK6jk+r7hKArqdJlKmmRxYiYpeeX8Z0y301Lp9uKNN2Dr1tMSuSozJioIgDUHsq0fpG4flJ5+9r5E0qwkphXRLcgTd2eVXjuffNKovPJVvUPxcHbgx20WdhW//bbopHriCRsnWD/L9mQS+9wq2xLCjRB/vJC+7X3V6TB9/nnROBIR0ehhcRE+KArsSbOyOWfqVFEI+/vv1p3fCmk9ybL27YWOZwsmOlRklvdnWmmY2crIKq4iu6T6lCEhAL17iw/G8nLxs9EoNldTpzZYRT6xdyg6rYbFiRn2maizs9Dnr5OckkgkrYZFO9Nxc9Lx5g29Adld1lZYnJCBs4OW8THB6g3aqZOQHLEiCDiiWwAaDaw9WL/sycL4dHzcHBlbu4Gtl4ICIaPw4YeQnS2KTABGjTqr2MTFUcdlPQNZuf+kdVKMZ+LvL5JXt90Gzz3XoI9YnV/ZoE42+JWtWgVffSWqGCVtmlAfVybHhfHTjrRTcmNqYjQpbDmaz3NL9zHktbVM/mgTX248RoSfGy9dE8P2J8aw8J5LuWNoR9v8sFoxfSN92ZdRQrXBxoTNwIFCjtHNsufZYDSRWVRFhJ8NnWXx8WI/chElywAmxIZQVm3g3yPWeb3ZFUdHcY/q2VMUQPz2m5AXkqhKfplePb+y2mSZb//eOGg11heVaTSiQ3TzZnXmJamXOgnG+0Z1IdDTmb8P2pDwkJhFjdHEe38fJibMi8ujG1mn20penui00Wjs2u3c0d+dLoEerN5v42tn1y6xN/r1V3UmJrEJk0kh8cxGBVuprBSyfZMmiYKIenB3dmBSXCjL9mRSXGFBw0h4uCiuefdddeZ6BhV6Ay8uO0BZtYH529Tvdi6uqOFQdin91ZBg3L//tC1Qnz6NHto7XPy/7k63UorRxwcSE+HFF607vxXSepJlP/0kAiktmOhQ0e6adIGlGMuqDdw0bwuv/3WQSn3LqTJMSBVv5PMMJrdvF5nzb74RPmWbNjU6jr+HM8O6+rM0MbNBCSub8PISEpF//w2rV6s/vkQiAeBkcRUzv4+/YAUFlXojy/ZkcUVsCFGhXvQI9mTlvguXLDucXcrNn29lx/GCC3ZNidjULtuTxZieQXi5ODZ9QlOYTEICsaREFHtYga+7E30ifFh36PxkWVGFnpX7TjI5Lgxnh0bG9/UVm4tnnxUyiTNniqRZPdRJMW5NsUGKsQ5nZ3G/vvtueP31etdix/MryC6pZmBHGyQYX30VwsJEt7mkzXPPyM7ojSa+3qSuREtVjZH/+3o7Uz/fyoLtqcSGefP2lN7sfGos398xkFsGtifAUwUfoFZOn0hf9EYTSRkq3M+NRvj+e+GfZSZZxVUYTYptnWX//CO+jxhh/RjNwODO7fB2deTPlibFeC4rVsB118Fdd5ntfSkxj9yyatqp4VcGcOAA+PvjEBRIsLeLdZ1ldTz4oPDAK5DrXnux4XAukX5udPR357KegWw4nIfeIBPS9uSX+HTSCip5ZGx3+0owP/64KCy/AB6aY6OC2HaswLIEx7nExYlk2auvSh+kFsCx/HJKqgz0iVDJR+unn8Rn+ezZjR42dUAk1QYTvydY6A0/YQIEBYl9tl5vw0TP5tN/UjhZUkXXQA9+iU+zvajrHHalFqIo0L+Djc+zogjZak+JgBO1AAAgAElEQVRPsxJY3m6OdPJ3PxVjt4ru3aXNwRm0nmTZ88/Dl1829ywaJcDTmW5BHvwSn26fpE4DfLv5OFtTCvh4/VHGvftPvcG45iAhtRBnBy09Q87Rco2NFa3bM2aIQF+nTk2OdU2fMDKKKu0XdL7nHujQQVTNywpIiUR1yqoNzPhmByv3ZfPumsMX5Jor952krNrA9f2EtN2EmBDiTxSSU1p1Qa7/9aZjbD6az03ztjJvw1G7amdLTvNvch755XomxYWqM+Cnn4rOh+XLbRpmdI9A9qQXk1t6dqfM0t2Z6A0mbmhIgrEOjQbee09U+mVmikBkUP0VriO6BeDupOPPvSoFUzUaeOcdkTCrp8t/W21SblCndtaNv3UrrF8PjzwCTipVy0suajoHeDA+OpjvtpygVCV58xqjiVnzd7HxSB5PT4xi19NjmXdbf67tG463mwqJ9TZE3/aiwjVBDSlGjUZ4Vzz2mNkBt7Ta7pcIPxuSZXPmwN69ooP2IsJRp2VsVBCr92erHgRSlQkThEzwV1+JIogaaVOgFvllevzdVbpXHj4s/AOBcF9X25Jls2dDWRl89JE6c5Ochd5gYktKPsO7ic+s0T2CKKs2sP2YTE7ai2qDkQ/XHqFPpA8juwfY70Lbt4tY5113ieI4OzM2KgijSWH9YRvihlqtkFFOTGzxTQ1tgbokSpwanWWKIjqeoqNh5MhGD40J86ZXuDcLtqdZHuuoqoJhw0SsXwUyiir57J+jTOwVwlMTo8gv17Nyn7rdt/EnCnDQaoiLsPF53rJFNGvMnWv2OjQuwofEtCLbYkqvvQaTJ1t/fiui9STLysqEb0YL5/7RXTmUXcoytQJUTVBaVcO8DSmM7hHIT3cPwkmnZcbXO5g1fxfZJRcmINwQCWlFxIZ54+RwzsvQ1VVUxoPYGJvRZj42Kgg3Jx2LEzPtMFNE5fwLL4h28hbujSeR1JGcU0pZdcvXCTcYTdz/4y4OZ5cytIs/aw5k201D+kx+2ZlGhJ8rAzqIbpfxMcEoCqxSedFUH1U1oqttfHQw46KCePnPg9z13U7bKvgkZrEkIQNvV0dGdg+0fbCMDHGfGjsWbrrJpqFG9RDzWX9OQcvC+DSiQ71Odac3Svfuovti61YYOrTBw1wcdYzuGcTKfdkYbJVirMPNTfi1hYWJopIzFupbU/Lx93Cmc4CV67RXXwU/PxEkkEhquW9kF0qrDPyw1XYZFaNJ4T8/J/L3wRzmTormjqEd1fN0aIMEeroQ7uuqjm+ZVisSV4mJsGaNWaekF4iAvk2dZTqdMFW/CLkiNpjSKgObk1XoHrYXGo3YW732mqhQv/56ERiT2Ex+ebV6Moxr156SUQv3dSPDlmRZr15CGnrBAnXmJjmL+BMFVOiNDO8qkjZDu/jj7KC1zXtK0ig/bU8js7iK/46zY1eZ0Si8HoOCTsfI7ExcuA8Bns6sslWK8ZZbxL7g1VfVmZjEahLTCvF0dqBLgAr+utXVYp85Z45ZnUhTB0RyKLuUXZZ2Pbm4QOfOwqfv4EErJ3ua11aIMR6b0INhXfyJ9HNj/lYL5f2NRkhteN+x43gh0aFetnuGDh4M69aJpg0ziYv0Ia+smowiG+7TAEuWwKFDto3RCmg9ybLy8osiWTYxNoTuQZ68u+awegGqRvh603GKK2t4aEw3BnVqx58PDuORsd1YfSCbMW/9w7ebj2O8gF1udegNJvZmFDesmXvnnWJDbKapt5uTA5dHB7N8T6b9qihvvhmeeabRAKRE0lI4eLKE8e9u5KZ5WyhvwQkzRVF4duk+1h/KZe6kGN64oRcajYbvLV24WEh6YQWbj+Zzfd+IU0bM3YI86OTvfkF8y9YdzKG0ysAtgyL5+Ja+PDMxivWHcpj44Ub2pl9Yqd62RHm1gZX7srkiNuT8Qg1rmD1bVMN/8onNsgVRIV4EeTmf1f29L7OYpIwSbrykcVPfsxg16lQVeGNcGRtMQbmerSkqVxyXlQmZpQ8+AOr8ygoY2MnPukCCosD48aKyzkOFDZ6k1RAb7s2wrv58+e8xqmqsX/uZTAr/+3UPy/dk8fiEHtx6aQf1JtmG6Rvpy64TNsjBnMm0aaJ47vXXzTo8rbACrQZCfFysu9727SI4efLi9DEd0sUfTxcH9bqH7cmjj4pOoxUrxPMusQlFUWo9y1SSYdTpTlW1h/u6kl1aZdtee/JkIe2YnKzO/CSn2HA4Dwethks7iy5+VycdQ7r48/fBbKleYQcq9UY+XJfMwI5+DO5spXKCOXz5pfDQfPNNYQ9yAdBqNYzpGcg/h3Jte787OQlViI0b4ehR9SYosZiE1CJ6RXifinvYhIsLvP8+TJ9u1uFX9Q7F3UnHgu1WFLe98YYoyLz/fpvkPHeeKGDp7kzuHt6JcF83tFoNNw+MZNuxApJzSs0bpKYGpkwRimOLFp33sN5gYndaEf072GA7AMLaAUTXnoP5Sbe6brbdaTbEkqZPF/f9r76yfoxWgkyWXWC0Wg0Pje1KSm45S+zVBVVLcWUNX2xMYWxUELHhoiLd2UHH7Mu6suo/w4mL9OHZpfu45uNNF9xHbX9WCXqD6Xy/sjq0WrjsMmEEbSaT4kIpqTKw/lCuSrM8B51OtACHhdlnfIlEJYwmhf/9uhdXJx37M0t4YEFCsyTFzWHehhTmb0vlnhGduXlgJCHeroyPDuan7alU6O2X5Pt9VwaKAtf2Pf1+1mg0XB4TzJaUfIoq1NPGrvf6CRkEejozuLM/Go2G24d2ZOE9l2I0Klz3yWa+33ri/9k777AorjaKn9mld6R3AekIiNhrUOy9l9iNNcbkM5YYjSZqEhNjEqNGjS0aazQ27FhQFBEFRFCKIL33Xne+P15QUcqWWUXc3/PwoOzOzN3d2Zl733KObGErBa4+SUdpZTVGtuPgOn7qFP2sXUtVbxLCMAw+stPH7agsVNYU0/z7IAkKcjwMc+VIMvIVetvpQ0WBj/NcB1NVValDfOlS4NEjJOSUIK2gTHwJRoahqroFC7gdp4wWwfze1sgqKse/D0X0QqiBZVl8ey4cJx4m4bM+NpjbS/LvsgzC3VwLaQVlSJG0whUghYfPP6dCuocPm3x6Yk4JjDSVIc8Xc6nr7U0Su8rK4m3/jlGU48PLwQBXnqS/uJ80axYsAKKjgZ496f8yyXuxKSitQpWAhS4XybLgYGD+fCCJrq+m2ipgWSA1T4IOwKFD6feNG5KPT0YdbkVlwt1CG+qv+PF62usjMacUzzKK3uHIWiZH7icgs7AcS6TZVQZQF8tHH1Hh9lukrwPJeEpcVPfJJ3R952CtJEM8SiuqEZFWyI1fWXo6SeOLEKdQU5TD8HYm8A5NQX6piCo6BgbA99+TJOHx46JtW4NAwOK7c09goKGIea/M88e2N4U8n8GhACGSeFVVwNSpwH//AebmwJQpb3RfhaXko7xKgA6S+JUlJND+Dx8WeVN7Qw0oyPEQkiiBqoOhITBkCPmRf+Dy2C0jWVZVRaZ/70GyDAD6OxnCyVgDv1+LluoCZq/fcxSUVeHzvjZvPNZaVxUHZnbE7xPckJJXhmFb/fDduSdvTbKt1sOgwc4yMejeRhe6ago4HZzM2T7rJTQUGDuWErQyZDRD/r4bh0eJeVg/whnfDnPCtYgMfHsuvNklX86HpuKHixEY7GKEZf3tXvx9erfWKCirwulg6RQUsCyLE0FJ6GKl84afyUBnQ1QLWFyVVHaiEXKLK3AjMgPD3YzBf6W6y91cG96f9UDXNjpYfToMi4+GNOuuwPeR0yHJMNFShocFB4sFV1cK8P3vf5Lvq4bedvooLK/Cg7hclFVW41RwMvo7GUJLhXufLiV5Pjzt9XE5PI3bTneGoWo0HR1gwgQEPqEgWxcrMars4uMpYC2T5pLRAF2sdOBmpoVdt2JEPo9ZlsXGS5H42z8es7tb4ot65ssyxMe95jrLiRQjAMydC3TrJtT8OzG3FKbaEiS6rl8HPDwATSHkb5spA9saIb+0Ev4xzViK8VUsLOj3f//R5yy77otFVjH5nupyIcN49y7dg2sSASZa9J2SyLfM0pI6TGSyypySWViOJ6kF6GVb1zerjwNJfPs8bR6e9S0FlmVxKCAe7cy10NFSwi6Spli/njy/pJmQq4dubXShLM+Hj6RrYjU1+t4DVGRYJVvbvm3CUvJRLWAl99ECgO3bAU9PWqOJwKSO5iirFIgXq507F2jfHti6VazustMhyXiUlI9l/e3rSKzrqClioLMRTj5MQmlFEx2UAQFkx/PTT9TpuWEDYGtb5ykP4iix3N5CgmvC0qUkc9mtm8ibKsjx4GSsgZBECVUdZs8GMjIk9mN/32kZyTI+H3j+/L2pOmYYBv/zskVCTglOiFkJ2xR5JRXY6/ccA5wMG/Q5YRgGw91McG1JL0zsaI59d5/Da7MvLoWlST2oHpyQB0MNJRhpclexKcfnYYiLMa5FZIhesSAKxcXUdvvbb9I7hgyp8OnhICw5/uhdD0OqJOaUYNOVSPS208MwV2NM6dIac3pa4YB/PPb4PX/Xw3vBw/gcfHE8BO0ttPHLWNc6kgAeFtpwMtbA/rvPpXItehCfi/jsEoxpb/rGY21NNGGipYzL4dKTXjr/OBWV1SxG1NPd1EpVAXundcCX/WzhHZqCYVv9EJUupDSAjEbJKirH7egsDHMz5kaCwsqKpKNE6IBuiu42upDnM7gZmQGfp+nIL63EOI83z1OuGNzWCDnFFQjg2vxdVxc4eBCIjITxd19DV00B1uJo5P/yC0ldZkqpY1zGew/DMFjQ2xqJOaXwDhWtS3LbjWfY4RuDSZ3M8fVgB+lWhn+AOBhpQFGOx50Uo6Ym4Of3svuoEZJyS94ohhGa4mIKinh6ird9M6GHjS5UFfi4GPYeSDG+CsOQ7+bGje96JO8l2UWkjKCjykFn2dOnJPtmTN3ttQnopFwJfYWtrCQdmYzXuB1N86Rav7JajDSV4WSsgWsy3zJOCUrIRUxmMSZ2MJfeQUJDgTt36N8iSLFxhZI8Hz1tyUuck/X4nTvAqFGkFtHMCnhbOrWNCm6SNipUVJA/9aBBJEUoAs4mmmhrookj9xNEP5/4fPLOFCNpXFxehY2XIuBqqlmvsszkTuYoKKvCudAmirS7dQPCwiiZpatLxbIMA8TGAtlUlBQYl4vWOirQUxfz/nvzJnXPrVjxsoBIRNzMtPA4OV+yppwBA0jNwebDLiJsGckyhqEvq44UtYI5xtNeH25mWvjjWrRUPLZ2336OwvIqfO7V9AmuqSyPDSPb4uT8rtBUlse8fx7ikwMPJJ8IN0JwYi7cLbjrKqtlRDsTVFQJcEmaC8MuXYDhw2kRl5UlvePI4JSH8bnwDk3F2UfJ0k2mvkNYlsXXp8MAABtGtn0R+FsxwB4DnQ2x4cJTXGwG/hVxWcWY/fcDGGsq4a+pHlCS59d5nGEYTO/aGlHpRVKpiD7xIAmqCnwMbGv4xmMMw6C/kyFuRWdJrdP2dHAybA3U4GhUv+48j8fgU08b/DO7E/JLqzB86x38FySdwooPifOhqagWsBjhJqEE4717dA9I5z7woKYoh06WOrgekYHjD5JgoqWMrta6nB+nlt52+lCWl4IUIwD06QN26VJYPbiN3vryoiciMjOB3bvJq8hMBM82GR8cfR0MYKOvhj9vxkAgpOTwHr/n2HQlCiPbmWD9cGdZokwKyPN5cDHV5K6zrJaCApJjbICyymqkF5TDTFvMZJmfH1W+f/SRmANsHijJ89HHwQCXw9Pfik82Z4wcCYwfD/zwg8zjRgyyi6izTIeLzrInTwAHhxfBSSNNJfB5DJIllVbNzSVJuVOnJB+jDAAkwaijqgAn4zfXFn3s9RGUkIucYulKzH9IHL2fCFUFPga7GEnnAAIBMGcOMGbMO+2y9XI0RGp+GcKSCyTfWbduwDffkAfbsmWyhNlbJCQxD2atlCWX5z1xgta/ixaJtfnEjuaISCtEsDidTxYWJI1dUgIkJgq92U7fGKQXlOOboY71Fst2tGyFNvpq9Usxsizw2WfAmTP0f3v7uo+XlZGv2IgRYEtL8TA+V3y/sqoqYPFiep3Llom3D1CyrKxSgMg0CYqt5eSAX38FnJzE30cLoGUky7KySMc0IuJdj0RoarvLUvLLcCxQ+C+7MOQUV2DfnecY7GIEe0PhTUDdzbVxblF3rBxkjzvPsuG1+RZ2+sZwLhWZWViOxJxSbjRzX8PVVBOWuqpSk297wfffU+Xp999L9zjCUF4O5HFUtduC+c0nCopyPFRWsy22uu50SDJuRWViWX+7F1IpACVffh3vBjczLXx+LIT7wJUI5BZXYMb+QADAvhkd0Uq1/sX8UFdjtFJVwL67ccLtuKwMOHAAyG/cf7GkogrnH6diUFsjqCjUX6U3wNkQFVUC3IjgXrIkIbsED+JzMaKdSZPB2a7WurjwWXe4mGrif8cfYcXJUJRVcl9c8aFwOiQZ9obqsDNUF38nlZUkHRQURGbDUqC3nR6iM4pwOzoTo9ub1pHq5BplBT48HfRxOSxNKr6GiV+sRL9pW+DStrXoG2/ZQt9rCRYMMj4MeDwG83tbIzK9ENeFuG4fuZ+Add5PMMDJED+PceGm01RGvbibayM8JZ/be9dXX5HvUUb9n3VtIN+slZjqFbm5JBklhgROc2OwC3UP773TfJQFhOKXX6hr+7PPZAFVEcniMln29Ckly2qQ4/NgqKEkmQwjQF2i164Bx45JOEAZAPnx+D3LQncb3XrvZ30cDCBggZuRMilGLigsq4R3aCqGuhrXkXTjlP37qcN540ZASUk6xxACT3t98Bjg6hOOFFfWrgU+/RTYtEnWPfwWCU7IgxsXsdetW6nbyMtLrM2HuRlDVYGPw8J4hNUHy1Ih04QJQnmbJuWWYOetWAxzNW5QGpFhGEzuZI5HiXkIS34ljsSy1F31xx/A/fv1H0BJCfj5Z8DPD0WTpyK3qEx8v7KAACpQ+eUXifxya2Psj5I4iA8HBgIXL0q+H1GJjgamTwfc3ambDyBJyD59gP79yVNtxAgqJqjxVMXVq1RgwKFFRstIliUlAV9/TRO694geNrro0FobW68/43QRuetWLEoqq/F5H9HbJuX5PMzpaY2r/+uJbm108MPFCAz9ww+JOdx1mUnDr6wWkpY0xr3n2ZyO+Q0cHYFp00iCS0S9XomprqYL18aNQL9+gLY2oK8vq85rhIfxObgdnYX/ednCUEMJF8OkJ7H3rsguKsd3556gnbkWpnRp/cbjSvJ87J7qAQMNJXzy9wPEZ799z72yymrMOfgAyXml+GuqByx1G/aZVJLnY1JHc/g8TW/6u5yaSlU906aRrnsjXApLQ1F5Vb0SjLW0t9CGrpoiLknhPDkdQjrdwnY36Wso4dDsTlj4kTWOBiZi1Pa7iMsS87NjWSA8nBLs7xksy0qUzInPLkZwQl690pci8fPPNGnbvh1QlyDp1gie9uQvwbJkPCxtBrc1QnZxBQKec9/FeS+pAAVKauhsqk7vWbWQc53CQlqQjRhRJ1AnQ0ZDDHU1homWMrbffNaovMuZkGSsPPUYve30sGViO8jxW8ZSqLnSzlwbldUswlMaL2QRic8+o/vYH3/U+3DtnEFsGcYJE0hW5z3xwm4MLwcDDGpriB8uRkhVXppzTEwoqHrhAvDw4bsezXtFVo0MYytJvU5LSigQ+FpluYm2suTqMzweJbwvXiRZLxkS8SS1AFlFFW9IMNbS1kQTeuqKuCbzLeOEc49SUVpZjfEdpKR6kJsLLF9OBRtTpkjnGELSSlUBHhatcIUrL2+GAX7/nTpLv/76vWp2eF9Jyy9Dan4Z2knqV5aRQd3en35K13AxUFOUwzA3E3iHpoin9MQwwPz55Kf5999NPn3jpUgwDLB8oH2jzxvlbgoled7L7jKWpWLNLVuAL75oPL40fjzw449QP3UCX946KL5fWbduQFQUSZVKgFkrZbRSVUBIAgfJsmXL6PMWIjHJCXFxwMyZtPY/fhwwNAQUa7ohq6tp7p+fD6SlkQ3X06dUyAzQvN3bm3zljh7lZDgtY4VYa/T8ni1qGIbBkn52yCgsxz/3uEm4ZBWV44B/HIa5GsPGQPxAnqm2Cv6a6oEdH7dHcm4pVtVIu3FBcGIe5HgMnE2kY5o9zsMMinI8fHvuiXS91779llrJdaUnkQWALtYREcCjGq+t7GygY0fSsk1JoS6HKVNaRAWstPjNJxq6agqY0sUCA5wN4RuVKTWJvXfFOu8nKCqvwsbRLg12ouioKWL/jA6oZlnM2BeIvJK3t0AVCFgsPRGKwLhcbB7nKlSL+uTO5uAxDA42dn0MDAQ8PCiB0dRkBsCJh0kwb6XSqBkzn8egn5MBbkRmCF/I8Phxk09hWRang5PR2aoVjLWErxiS4/OwtL899k3vgJT8Ugz5w094OU2BAPD3p8mOrS3g7EzVvIBUZAS5gmVZxGUV43BAAj49HIQOG3zg8M0ljNx+B9+eC8eZkGQk5pQIfY0/HZwChgGGuRqLP6joaOC776iKaehQ8ffTBFZ6amijr4YeNrriB3tF4KMaKcYLUpBivBebjVaqCrAJ9AUWLiRZLWFITaXKxa++4nxMMlom8nwe5vayQlBCXoMefJfD0/C/44/QybIVdnzcHgpyLWMZ1JyplVwP5mLRXoudHUnhbtsGFBW98XBiTdeLWDKMAkGL6mTi8RhsHucGV1MtLD4ajFAuKo3fFp99Rh43Hh7veiTvFdnF5dBWkZe8EEBFhYJRS5bU+bOptrLknWUAzaMKCoBbtyTf1wfOrRq/sh629cckeDwGfez1cSsqExVV75EkazPlWGAC7AzU4SZp8qEhVq8GcnLoHtcMJKK9HA0QkVbIXSE6j0edcz4+b8rayeCckESO/Mr09YGEBIo9SsCkjuYoqxTgTE0BschMnUpxz2XL6HvSAA/icnDuUQrm9LSuo7hUH5rK8hjmaowzIckoLK0AVq2i7seFC6nTq6nv4bJl8O87Ggvv/QtrXzE6saKj6belpcTfeYZh4GqqiRBxpC5fZ/ZsSkL5+kq+r6YoKADatgUOHyaZz+fPqWCq1jdt2DCSSb93D3jwgGLj4eH0ngHA3LkUG8/MpN8c0DJWie9psgwAOlvpoFsbHezwjUFJheTB+123YlFWWY3PxOgqex2GYTDA2RCf9bGBb1QmbnDUuh+ckAtHY403fIq4wlhLGf/zsoXP03SpdIa8wMyMKmKkcd4lJtIkYsoUwNSUsutff02P6esDZ89SMDEsjKpz9uyhv1dV0YXk33+5H9N7yoM46iqb29MaKgpyGChFib13xY3IDJwOScH83m1g20SS3EpPDbumeCAptxRzDjyUimdifWy6Eolzj1KwfIA9hrgIl7Aw0lTGAGdDHL2fUP/1MTgY6NmTpHru3gU2b6bqk5wcMl99rYMqKbcEd2OyMaa9aZMSiAOdDVFSUY1bUZn1P6G6mlrzAwKA27cBV1dg3bpG9/koKR+xWcX1mssKw0f2+vBe1B1t9NUw/1AQ1nk3URAQH0/Xj65dSXfaygr480+gQwe6RrRuDYSEiDUWaZCSV4qTD5Ow5PgjdPvxOnpvuomVpx7j/vMcdG+jiymdLSDHY3DkfgIWHw1Bj59uwGO9D2btD8Qf16JxOzqz3io1lmVxJiQZnSxFS1K+wapVVGW9ZYsEr1I4Dn/SCVsnukv9OABJMX5kr4dLYemcSzEGxOagk2UrMCNHAhMnUqeAv3/TG9ra0nerQwdOxyOjZTPOwwy6agrYfvNNnyPfqEwsOhyMtiaa2D2tg9TmoDLqoq+uBFNtZe7ln5cvp+r73bvfeCgppwQKcjzoi2Ow7u0NmJsDkZEcDLJ5oCTPx19TPaCrpohZfz+Q3G/qbSEvT/MXQOYRLQLZRRWS+9K8ymvzZVNtFaQVlEmedOnbl+ZU585Jth8ZuBWVCQcjDeirNyzX52mvj8LyKgTGNRxcltE0T1IK8CgpH+M7mEnP69TamhIBrq7S2b+IeDkaAAB8uLSxkJd/6Qt6+TJw5Qp3+5ZRh+DEPCjwefX6GQpNWRnFPhQVJZIIBIC2pppwNtHA4YAE8RobeDxSK8nNBVaurPcpAgGL77yfwEBDEfN6WQm128mdLFBSUY3TISmUX/jkE1rzC/M9Zxis6jsfp0bPBzNokCivhmIx9vbAvn2ibdcIbmbaeJZZhMIyMbr3XmXUKJJN/vFH6nrjmrQ0UpIBAA0Nimk/e0ZxKwMD7o8nIi0jWVZbVfgeJssA4H9edsgqqsDfdyXrLssoLMMB/ziMcDOBtZ4aN4MDMK1ra1jqqmK99xOJ/cuqqgUITcqXvA24CWZ2s4STsQa+ORsuXouvKJw5Q9WPkpCZCdy8+fL/48cDM2bQ5KFHD2DXrrpyM0OHUlvq6+TmUrfIuHGk81oogbFjC6G2q+zjzhYAAI/WraQmsfcuKCqvwqpTYWijr4aFH1kLtU1Hy1bYNM4V9+NysPTfUAik4FX0KkfuJ2D7zRhM7Ggu9ISllhldW6OgrAqnguupPnJ1pcVEYCDg4vLy7z4+VA00aRIlkGv4L4j2Mcq96WRVZysdaCrL41J9skVVVST5+PvvdKyuXSmx/c03jSbMTgcnQ0GOh4FtxTeDNtVWwfG5XTC5kzn2+D3HzdpkXlERme5+/PHLbhwzM2DgQOCff+gac/kyMG8eoKdHms+amnSdqZTyNbIBMgvLce5RCr767zF6/3wDXX+8jiX/PsL1iHS4mWth3QhnXFvSCwEr++C3Ce2weogj/p3XFY/X9of3ou5YP8IZH9nrIz6nBL9cjcKUPffh+u0V9PnlJpYcf4SD9+IRlpyP4MQ8xGYVCy192SA7dtD13khKZt6voK+uBE0Veakfp5ZBbY2QVVSO+w105IhDYjn0Oc8AACAASURBVE4JkvNK0dlKhxYaf/5J5+SkSY17Cz58SIHRZlBNK+P9QkmejxndLHErKhOPk16eYwGx2Zh78AGs9dXw94yOUJOWx4iMenE310ZQPMcdTZ07U7FMPQUfibklMNVSFs+L7vp1uv60bi35GJsReuqK2De9A8oqqjFrf6DkAZS3yZEjLS6BKU2yiyq48SvbuJHWo69hqq0MliVpL4lQVQVmzSLJTRliU1xehYfxuejZQFdZLd1tdKEgx+M24fEBcvxBIhT4PLELH4Xiiy+EV2J4C7TWVYWNvhquciXF+CoCAXXSjRwpXDGdDJEJTsiDg7EGFOUkKBL79VegTRvq/uGAiR3NEZFWKH73k4sLsHgxxTprE26vJN5OBScjNCkfywfYN+hR/8YuTTXRSZvBoYAEsJs307pfSLnJzMJyxOSWIWPRErq3FRYKN2dhWYojt2pF1gMc4WauBZZFnbWQWCgrU3f5lSvkU1f7Hktq65GZSYXtVlZUfF6biBs3jgq9mwktI1n2HneWAeSP09tODztvxUi0eNlxMxaV1SwWcdBV9ioKcjx8PcgBMZnFEstFRqYXoqSiGu4WHBhMNoIcn4cfR7kgu6gcP16UshZyeDglsvz8hN8mOxs4eZJaTNu2pa6w/v1JHx6gdt/QUMq2Hz1KlQ21LaaNoadH41i9Gjh4EHBzk9rEI6OwTDzN+oSEt+avFhiXA79nWZjXyxrKCjRB4PMY9HcywPWIDJRWvJ2uKmmy6XIkUvJLsXF0W5EmQcNcjbFsgB3OPkrB5qtSqBSpwTcqE6tOh6GXrR7WDXcSuQqvvYU2nE00sP9OHFUf5edTIjgxkSYw335L5/2rjBtHk7r//qPnVleDZVmceJiErtY6MBVCmkmez0NfBwP4PEmvWz1bUUF+JocOARs2UMcnnw/s3UuyAN98Q1J9r1FZLcC5RynwcjCAhpJkSRAFOR7WDHWCoYYSQjbvpm5SPT1g7Fjg0qWXExkejyp0Jk8GtF4rUGjViiaBISFULfQWKKusxuXwNKw9G45+v/qiwwYfLDoSDO9HKWijr4bVQxxx4bMeeLjKC9snt8eUzhaw1lN745yR5/PgbKKJjztbYNNYV/j8rxceremHg7M6YomXLVrrqOJmZAZWnw7DkD/8MGr7XSjwJUhSFhZSglRbG+jVi4N3ovnhaa8PJXkep1KM92LJA62zlQ79QVOTpBUSE2mBUx/V1fT9klCvXcaHy5QuFlBXlMOfvs8AACGJeZj19wOYaCnj4KyObzUJLYNwN9dCWkEZUrjuaLp4kVQYXiMptxQm2mJWPt+4QfI+ihx25jQTbAzUsf1jd0RnFOHTw8GokrAA8q3h6QkoKNCaqQVJZEqLrOJy6HDRWXbzZr2V5KY13y2JfcsAqihftkzy/XzA+Mdko7KaRa8G/MpqUVGQQzdrHVx7miFdm4oWTFllNU4FJ6O/syG0VTlISL/OyZM0T26Gn4+XowECnucgv4TjQgsejxSTjIyAwYNJNUkGZ1RVC/BY0kaFqioqeLS2pu4fDhjmagwVBT4O13qEicO6dRSLYRgqtLSzAzZvRnFqBjZeioCrmZZIhbLMr79i3y8zURAVg6DEPJF82R7GU7HpC5uRSZOoMDkpqfENjx0jhaLvv6c4A0e4mpLdUTAXUoyrV5Mk4oED9F4LBDQv09GhBN+uXU2/zloKC0mpx8qK4t1jxpDdkK2t5OOUAi0jWTZ+PBkOCpNMaKb8z8sWeSWV2OsXJ9b26QVl+CcgHqPamcBSl/ukYR8HfXRvo4vffKKRWyy+z1GtZ0E7M+kmywBq8Z3V3RJH7icgoCZoJxUWL6YurxUrGp7cZGbSBKi2mn73bro47N0LGBujct16JP13/uXivEsXSqKJY54pL0/Bel9fupjNnEkBSA5Iyy/D/jvPMW6nPzp9fw09frqBVacfN+59xbKkKfvdd4C7O2BhQcmM2sqUX36hiWEp97Iwv/lEQVdNEZM7WdT5+0BnI5RWVsO3IYm91xEIKClTj9zPuyQoIRd/+8dhSmcLscxE5/eyxsSOZth64xmOBb4yWbl2ja6nnTpRm3sjetCN8TS1AAsPBcHWQB3bJruL5Z/AMAymd7VEdEYRgnzuUzX5oUMk0dYYn39OE6hDh4D58xH4PAcJOSUY0174apUBzoYoKKt6EfRHWRkF8U+epGTcq63/tQmzadOANWve0Ha+HZ2J7OIKjOCiElEggIIcD7O6W8Lwni8qgoJJp/nGDUqwC5v8GjGCEhPr1gnluSYJ2UXlGLfTH3MPPsTRwAQYaChh2QA7nF7YDcHfeGH3tA6Y1d0SjsYaYnUDaCrLo4eNHhb1scGe6R3wYJYTAnor40SrROzK9MWx7BvQPPGK2WtyMl2Xhbk2LlgAdO/O2XW0OaKiIIeP7PRxMSyNMynGgOc50FaRh43+K53uXbpQkvY1D5QX/PcfyS9I2q0t44NFQ0keU7pY4GJYGi48TsW0vfehrSqPQ7M7cytNJkNoagvkOJdiVKkpfElOrmM+nphTIp7fY2YmFap5enI0wOZHDxs9rB/hDN+oTKw9F/5+BM0NDMiP9upV6qCX0SjZRRXQ5SKQ//Qp4Oj4xp9Ntei7xYlvGUCBWGEDbTLe4FZ0JpTl+WjfuunYiqeDARJyShCT+abXo4ymuRyehvzSSkzoYMb9zvPzyR9py5ZmmSzr62iAagGLm1FSsLEwNKTru7Iy0K8feSTJ4ISo9CKUVlajnSR+ZWfPUqHjokWcjUtdSR7D3YxxLjQFBeI2i6iovFQBqKig5oMlS6DQ2hzLjv6IH01KIHRIYetW2rZHdxTrGODQPdGSeA/icqEox4OzSU0yccMGinUOHtxwN15xMfDllxQfnTlTpOM1hZaKAix1VbnxLQPofa4tGGZZkoycNo2KrufOJeWY77+nxwWCN2Mmr17Tdu0CBg2ihpMDB6hjsZnSMpJlCgpUVS/3/sqquJhqwcvRALv9YsWq2PjzZgwEAhaLPLntKquFYRisHuKIwrJK/OYjfhdKcEIedFQVYNZKMq1bYfnCyxam2sr46tRj6XkzqapScPzOHfI6AChr/nrn2JgxFMwGqNrA3x+5yRnYsmwrOrMd0f12Of66I1nnXh26d6cL2KlTFMgvKaGqABFJzivF7tuxGP3nXXT+4RrWnnuC/JJKfN7HFtO6tMbhgAR4/uKLo/cTXsr5VVW9lHbbupU63NaupZvaTz/RxVFDgy6m+/ZR54uREUnE3bvHySTx/vMc3HmWjXm9rF50ldXSyaoVtFXkcSlMiC6KykqS2Fu7FpgzBwgKknhsXFBRJcCKk6Ew1FDC0v52Yu2DYRh8N9wZPW31sPJUGPlzpaTQDUxJiRKYCxfSZ1NrPCokafllmLk/EGqKctg73UMi2ashLkYYlBoK+xFeJI/k40Pfp6ZYuZJ+fHxw8UYo1BTlMMC5HvnSBuhhowsVBT4u1kp28vn0vuzYQcm41+HzqZPr9Ok3OpBOBadAW0UevWwbr/xskogISmJev44JHc3w66D5+GLjaeC334DevUW/D/7xBwWipHheJ+WWYOwOf0SmFeL3CW41XWCdsKB3G7iZaYlnQv/kCXXdbtpEBQujR5PkZA3MggUwGNgHHsvno9/en9Fu5880ca1l8mS6LsvLU2WUnR1N+mrZto32vWEDyVj270+fbwumVoqRKz+Le7HZ6GSp82byc/Zsui8CL2W0Abru//ADVZeNHMnJGGR8mMzsbgkFPg8LDgVBWZ6Pw7M7w1CzYS8XGdLFwUgDSvI87qUYAVJPsLQkE3CQNHVuSSXMhOggf4NaOfQWnCwDSP5obi8r/HMvAXv8RF8XvBPmzaO1xBdfyCTmG6GiSoD80krJO8uKisj31sHhjYcMNZXAYzjqLAOAAQOEm9PLqJdbUZnoYq0jlLpIH3t9AIDP05bj2/02ORaYCLNWyuhSq5jAJWvWUPH/tm3iFUtLGTdTLeipS9HGwtKSpN7Kyzn1bvrQCU6kIiU3STrL/viDit2HDOFoVMTEjuYoqxTgTH1WG6LSpQvg54f02/dwwrkPhjzzh8O0MS+L8RuLLe7aRTHb4cMhd/QIhrU3h/fjVJEaRALjc+FqqvXyOuziQv7w4eHUJFCf5UVoKMVnt2yRSozBzUwLIYl53BdF8fkUK9y2jWLLYWEk29ynDz1+/z7Flj7+mBoiNm4kW6HqakBdnTrWjx2rd37R3Gh+V2JxuHyZpLCaYRWGKPzPyxaFZVX467Zo1RSp+aU4HJCAsR6mMNcRY3EoJHaG6pjUyRz/BCQgKl28hUpwYi7amWtJzxD1NVQU5LBhZFvEZhZj2403Dd85Y9YswMaGOo9YlirkXukcw/ffA3fvUnUBgERVHazNUEfXX25j89UouJhqoq+DATZceIr13k+485DS1CTDSIBaaF1dKYPfxHclMacEu27FYMS2O+j243WsP/8UpRXV+LKfLXz+1wuXv+iJxX1tsHaYE7wX9YC1niq+O3ofG+f+gNwxE+gCefo07WzoUHpfUlNJInLp0pettjwe3SiuXycpuQMH6GZXW5kgAb/5REFPXfGFV9mryPN58HI0wLWnGY0nUUtLqZPo8GFKlu3eDbRrJ/HYuGCHbwyi0ouwfoQz1CWQ9ZPn87BtUjvY6ShhwaEgRPDUKNF7/z51BAYHU7t0bdXH119Toig4uMHzqKi8CjP3B6KgtBJ7p3eAkaZkyXGli+ex9Z9VSFDVQcrVW6JJ4a1fjxL/AByPL8dgZ0OhdasB8r/5yF4fd4NiUJ2aRomVf/+lCpqG4POB4cPp38HBwE8/obCsElfC0zDExRgKcmLedlmWJnPu7jQxKS+HupI8Rva0w8WwNCRkixm00NWlScuriSIOiUovxJg//ZFZVI5/ZnfCcDcT0TXTKytJpsfYmCrHAJKDmDiRrid791IFNMu+7C5YupSCp6Gh1BlZUkIyB7UsX06T/2++of20a1dXznP7dtrHqlV0Da31gWvB1Eox/uYThbJKyYpLknJLkJRbik5WjXS8fvEFJXhrP9OrV+k7s2xZi09MypAuumqKmNndEgYaivhndifxuoxkcIY8nwcXEy3uO8sAwMODCno2bgRA81cA4hXlWVkBn34KtG/P5QibJcv722OgsyE2XHiKK/V5szY35OTovpydTespGfWSUxPck9izrNZrpZ7OMgU5Hgw1lJDIVWdZr16kFpH2HpyHzYyE7BLEZZegp03jfmW1GGspw9FIA9cbS5YVFFAnp+zzqEN8djHuxmRjXHsz8fwwGyM0lNYkc+c22/sPj8dglLsJLoWnSe6D1BBOTiSnV4+dgQzxCEnIQytVBZiLOw8OD6dCogULOF+btTXRhJOxBnmEcRTHX5cgj28HfYrcqOfUxKCiQvGB7t2puPbp07obnD1L37tBgyiBIy+PyZ3NUVElwMkg4TqeSyqqEJ6cD4/Xu3v796d4xeXLFE94nS5dyJ6mWzcxX23juJlpIbOwHKmS+os2BsPQ93bZMirmBqiRZPBgSn5PnkzqaxoaQG7NGuB1a5DmDMuy7/VP+/btWXbZMpZVVGRbAgv+ecg6rr7IZheVC73N16dC2TYrz7OJOcVSHBmRXVTOOq+5xH68+x4rEAhE2ja3uJy1WO7Nbr0eLaXRNcziI0Fsm5Xn2ci0Aukd5OxZll20iP4tELCsvz/LVlTUecrjpDz208NBrOUKb7bNyvPskuMhL8ZUVS1gvzn9mLVY7s1+diSILa+s5nZ8cXEs27MnywIsO24cy+bk1Hn4eWYRu+1GNDtky23WYrk3a7Hcmx2y5Ta7/cYz9nlmUcP7LShgBYMHs1UKiiwLsDlK6uzD3kPZ/Jt+oo8xP59ld+9m2YgI+v+1ayw7aBDL/vsvy5aVCb2bezFZrMVyb3b37dgGn3M9Ip21WO7NXnua1vCOrlxhWT6fZbdvr/v3uDiWLRf+O8o10ekFrM3KC+ynh4M42mE0W+HozH4xZR3b+XsfNi2/tOHnzprFsgoKdB61bcuymzaxbGoqm19awT6Mz2GP3U9gx+24y1p9dZ69EZHOzfjy89mihZ+xzktOsOu9w0Xe/MSDRNZy6Rk2Y+wklt2wQaRtL/k+Zh8ZtmGLnFxYtqpKtAMvXsyyABv2yeesxXJv9kFcTtPb1EdWFsuOHEnved++LJuc/OKhtPxSts3K8+zq04/F2/ernDnDsuGiv78N8SAuh3VZe5ntsP4q+yQlX7ydpKW9vG6NHk3XCJZl2dhYlg0Le/l/rhEIWLaggGVjYuj3B8KJB4msxXJvdsa++xLdg2r30+jn/t9/9LkuW0b//+YbljU1FelaL0NGQwgEArayiuN5lAyx+f7CE7bNyvNsaYWI91Fh+P13upbcucNeDktlLZZ7syEJudwfp4VRUl7FDtvqx9qvusiGJua96+EIR0bGux5Bs+ZxUh5rsdybvfg4VbId+fuzbPfuLBsZWe/Ds/YHsp02+LBV1aLFAuolJIS+v7t3S76vD4wD/nGsxXJvNiajUOhtNl2OYC1XeLM5DcWaZs2iz8PWlmUTEzka6fvPT5eespYrvNmUvBJudywQsGyPHiyro8Oy2dnc7ptjCkor2PbrrrIjt/mJHAcUmagolp0wgWWLGolByWiSPr/cZGfsuy/+DqqqKMaZlcXdoF7hYM017ItjwWx0uvDXsfq4/zybtVjuzW6+8tp9q6CAZSdNYll5ebq29e7NsseOUSyvoIBlV6xg2dK6sa/R2++wvX++IdR5fudZJmux3Ju9/rSBuNcff7BsfHzdv125wrLV0l2jBCfkshbLvdnzoSkS7efi41R248Wnom9YXc2yAQEsG8RRvFJEADxgJcw1tYzOsuJiymC2AD7va4OSymrs9BWuCyoptwTHAhMxzsMMpuJIjohIK1UFLO5jg9vRWbgRKVoLf63BoESauWKyeogj1BTl8NV/j7nr2nqdoUOpjRagLHvnzoC8PFiWhW9UJibvvochf/jhRkQGPulhhdvLPLFprCtsDdQBAHweg7XDnLC0vx3OhKRg1t+BKCqv4m58FhbUwfXDD+QL4+KCnGu+2Ho9GgN/v43em27ip0uR4DPAmp4muDvZFucWdcf83tZofekUVUTMnk2vs0OHl50oampgysvBXzAfxVd8sPWIH8Z2mYeevsU4HJAgmv+NhgZ16dnVyApmZ1N309ix1FWyaBHJxTVRffKbTzT01BUxuZN5g8/pZq0LdSU5XHhcT+Vcrc6ulxd13cyf//KxtDSSglm+XPjXxSECAYvlJx9DRZGPNUPfrPgUmfPnAQ8PyKel4LNBbVFQWokZ+xo+9/L/+BMh95/gwbL1SCpngC+/xMkRc+Cy9gpGbbuD1cce4FFSHn4Y2Ra97fTFH1dqKlX6lJQAGhpQ3fo7erlb4mhgIopF/F6ceJgECx0V6Cow1Bn322/CbZiejr4LJ8IuMx6nR80VvaJq82Zgxgw4/fUb1jw8Dndxr33//kvVUZs2UXWSsfGLhww0lDDCzQTHHyS+qCgWi4IC0svmyOPwRmQGJu++B20VeZyc3xUORmIYAt+7R510gYEkhXjixEtjYUtLqmTiyGj4DRiGpAKsrOj3B8Lo9qZYP8IZ1yMy8PmxYFRVC5reqB7uxWZDS0UedgaNvHcjR9J3/KefSFr122+pglFR5islQ3IYhhFP4lWGVHA310ZlNYvwFClUpM+aRXK6Gze+6HYRuZswL486WwXiXfPeR5QV+Phranu0UlXArL8DkZLHvXcw59R2gN++/d4rykiD7Jp5oK6knWWdO9N7XKsE8hrD3YyRVlDGjSe4iwtgbk4V/jJE4lZUJky1lUXyq+/jYAABi4a9p4YNI9uBtDSgZ08gLo6bwb7HVFUL8O+DJPS205dYLaVePv+cJM1aie4//jZRV5LH8gF2CErIw+kQDqTzGuPJE+D4cZLZr5BgffsBk19aiWcZRWgniQQjn0+xPx0pSI8CGOthihndWuPC41R4/eqL+f88FKtzUSBg8d25JzDUUMLcXlZ1H1RXJw/7pCSKg8bFAePHkwqWujr9TamuVPvkzuZ4nlUM/5im73EP43LBMDTPrZdPP6V7nEBAFjlXrpA3n5TlRh2M1KHA54ntW1ZVLcAPF59i3j8PcScmW3TVGR4P6Nix2ahyiUPLWEW2oGSZjYE6hrsa42//OGQUNt0yue3GMzBgsPCjt2eMN7VLa1jpqmK991NUihBIC07IA48hf7a3jY6aIlYNdsTD+FwcCuDQF6wRKqsFOBWchEFb/DBt7308yyjCVwPtcfcrT3w1yKFe/wyGoc/y5zEuuBuTjQm7/JFZWM7doPh8YMUKCO76I0dVC1NPP8OmK1GYdWkP7p9bhWeHF+D0Ui/MGNwOxhNf8Yz580/gxx9J1iwpiW6YtYaaDEPyWb/+ClWvPlg9wgXnP+sOWwN1rDz1GCO33xHfXHLsWNLMv3SJbip//UVtvY0E8+/FZsM/Nhvze1lDSb7h5IaCHA99HQxw9Ul63fM4JYWSgZcu0f+tXrvhGhoCU6dSwuUdGI0fCojHw/hcrBrsCF1JPAkEApI5GDqUEg8PH6L1hOHYOtkdkemFWHQ4CIFxOTgckIC1Z8Px8e4AdPreB67fXsGIIxEYw7ih77gfMe/rg3g6eS6WDbDD8bYsnv41A0/S/sO4+2cpyePrS9doUXjwgD6Df/6hZGkNM7q1RmFZFU6JoG2dmFMC/9hsjPKwALN/P8lqfvEFSRo2RlIS0KsX+LGx2Pq/X7FV2U50iQAeD2m/bMUxFy/M8DkA5ttvhd+2ooICdwAlFB4/BpYsqVfHfk5PK5RVCnDQX4Jrm4YGSYAEBAC//ir+fgCcCk7CJ38/QBt9NZyY31V8CbSffqLEib8/tfHLeCt83NkCqwY74MLjNCw9ESpWgUnA8xx0bN2qaamazZtJ5qlfP/IjlFbyU4YMGe+U2iCCVHzLVFUpGHHhAnKfxUNVgQ9tFRHlqc+fp+KMkBDux9eM0VdXwt7pHVBaUY2Z+zku0pMWFy9SEP/QoXc9kmZHdhGtGSVaHwBNJiK9HA2gpign0ny8QRiGEjRXr1KBXAuCZVmcD01FXgn3wf7KagH8Y7LR01ZPJHsLFxNN6Kop4lpDUozDhgE7d1IRU14erZk+cHyjMpFRWI7xHcy43znD0Np0/Hju9y0FRrubwtVMCz9ciJDu/WL4cFqrX75M3vEcFHK+LZJyS7DH7zm8Q1NEf4/S0ijGdPAgWWLki19gFJpE8y03cYt1d+8m73cpvveKcnysGeoEv+WeWNDbGn7PsjB0qx+m7AmAf0y20LGXk0FJeJycjxUD7Ru23NDXJ0nAZ88opjliRIP7G+hsBC0VefwjRNw4MD4Xtvrq0Gxq3rlhAxWifPIJYG1Nnl5SRFGOD0djDYQkiD7vzigsw+TdAdjpG4uPO5vj+NzOjcZVWyrCm7c0Z1pQsgwAFve1xbnQVPx5MwZrhjo1+LzEnBL8+yAJkzuZw1hLClUuDaAgx8PXgx0w6+8HOOAfj1ndLYXaLjghF7YG6lBTfDen3Sh3E5wOScbGS5Ho62ggncogAMXlVTgamIg9t2ORkl8GG301/DzGBcPdTIT2KxrrYQYdNQUsOBSE0X/exYGZHdFahKqxxojJLMJXQZW4P/wHdLbWwbWRbWG96RZQrQcYOFMyyMDgZTIMoMSRqqrQhrP2hho4Nqczzj5KwYbzTzFy+x2M9zDDsgH2aKUqYrUjn0+av/37k9ZtRAR5F1RWUqB1wYI6nR+/+URBX10RkxrpKqtloLMhTgUn415sNnrY6AGxsUDfvkBmZuPdDT//TBOYmTOpIrKBykuuSckrxcZLkehho4vR7iaS7ez8eTIT/vhjWhSpUELjIzt9rBvujJWnHuNGZCYAQEWBDxt9NXRvowcbAzXY6KvB1kAdJlrKdYPh4eXA8GHk8bZ79yt/D6eA+Pbt5P2mp0cTFj09+lm3jqrpoqNpsbxkCZ2Dd++Sz14N7ubaaGuiib/vxmFyJ3OhFof/BSXTOqS9KZ03R47Q5GjePHrNDU1U5s2jxOnly2it3Bqp/z7Co6R8kQ1yz4Sm4scBizDI2Qjq9+8DVVU0jsaIjAQmTaLzMTYW0NZ+2W1ZDzYG6uhjr4+//eMwp6cVlBXEnMxMmEBVfKtWURK1kWM2xB6/51jn/QRdrHSwa2p70f30ysqoy01fn7zIBIJmX2nZEpndwwrlVQL8fDkSSvI8fD+yrdDBmOS8UiTklGB619ZNP1lFhb6T7u6UFB06VLKBy5Aho1mip64Is1bK0vEtA8iLYvp0RPhmwawVT3Rv5Bs36F77ypzjQ8HOUB3bJrtjxv5AfHo4CLunejTvrsz+/ala+csvgSFD3i//CymTXcSRZ5m7O9CnDyka1IOSPB8DnQ1xMSwN3w13Fn/eWcuCBdRBoiDhuJsZJx4mYemJUAxzNcaWidxW1wfF56KovAo9bfSafvIr8HgMPO31cDEsDZXVAsjXfteXLKFi2JUr6f8dOgC3btVRs/hQORqYCF01RXjaS6CYUh+rV9M8eMUKSpq9B/B4DL4d5oQR2+5g6/VnWDHQXnoHmzWLfKeXLaOYQEICvU9r15JKEp9PsSk+n2JB167RduvW0T299nElJfI23bGDHj98mIqxVVUBNTX6racHeHrS4/HxVDCgqgpoagp1XSosq8TFx2k4GZSEgOc5L/6uwOehWxsd9HcyRF9HA+gq8cmjLiKCfp4+pd+LF5OCU30JakNDKhgfMgTIyCBfNzs7Uo1qRPUmJCEPDAO4itNZVl1NHVfGxm/FR1pXTRFL+9tjbi9rHLqXgD1+sZj41z24m2thQe826OOg3+C8rri8Cj9djoSbmRaGuQpxveLzgYEDG32KkjwfY9ubYt+dOGQUlEFf480mBwCoo/54XQAAIABJREFUFrAIis/FcDchjrtgASVBo6OBc+feipKKm5kWjgUmoqpaIPS8LjAuBwsPBaGgrBKbx7lilLuplEfZfJEly5ohlrqqGO1ugkMBCZjT06rBpM4f16PB4zFY8Ba7ymrxtNdHDxtd/O4ThZHtTJpMgAgELEIS8zDE5d1NuBiGwYYRbdHvN1+sOROOXVM9ON1/QVkldvrG4KB/PArKqtDRshXWj3RGb1t9sYxgPe0NcOSTzpi5PxBjdtzFvukd0dZUU+zxVVQJsOtWDLZcfwYlOR42jnHBOA8zuvHUGKM3iBgyZAzDYLibCTzt9fG7TzT23Y3DxbA0LO1vh4kdzcEXxxxXW5vMMAEyG/3qK+qG+f13YNQo+Mfm4F5sDtYMdRSq+qGnrR5UFPi48DgNPSoySHaxvJzkKjt0aHhDBQVKKrRrB4wZQ3JxKtKVQWVZFqtPh6FawIoUuH6DsjKaNA4ZQtVaXl5vTNAndTJHa10VlFcJYKOvBmNNZeHOYScn4MABSnJkZVHSMTOTOtcAmtiNGkUTvcxMmixmZFClDQDs2UPnYs+e1LWnV3cByDAMpnVtjS//fYS7Mdno1qZxQ2uBgMWJoER0tdaBSW1BgYICcPIkMG4cTT4bYtcuSpZ5eKBvSSXkeAwuhaWJnCw7FZwMV/NWUP9hHyV45eSoclZZ+c2FEctSkvHzz+nxffvonBeCOT2tMH7XPZwISsKUzhYijfEFDENdpI6OlAi+dUvoCTLLsvj5ciS234zBACdD/DbBTfQKpPh4CpbIywN37sgCYO+YhR+1QWlFNbbeeFZT+eco1HWnVpapk5WQSU4XF1octqB5nAwZMt7E3Vwb92KpUljsOUxDaGsD2tpIOp0AM00xAhDXrwO9er2VoFBzpKet3otCqW/PPcF3w524/4y4gsej4qsOHYBvvnkpgS8DWcXlUJDjSVaYWl5OagZDhjT6tJHtTPDvwyT4PE3HUGEClI3h4EA/LYj0gjKs834CJXkezoWmYMFH1rA35K57/lZ0Jvg8Bl3biC6P1sfBAMcfJCHweQ66ttElyc3Nmylg/yrOzvS7vJwC+V9++cEVFGQUlOF6jYWGPJdFBOHhlIyYNeu9SZTV4mamhbHtTbHHLxbjO5iJJAMqMkuXUhzqzp2X75OBAXXmCASU1BEI6sroCQS05i4vp8fT02mdUcuBAxQDeRUHB5J+BEjN5M6dl48pK1NsolZ1aPFiIDMTAk1NJAoUEFIAXKrWwkWrjrDUVcX31gL0cjZGQWwinvs9RPHucNzXNMdXrl7obqCAg1/0o/3wePQ67O1fxjxsbCg2kp1NxbMREfTbtCZhcfPmyy5ERUV6vp0dnUs2NlRwqqYG8HgITsyDtZ4aNEQtXAWogzs2Fvj+e9G3lQANJXnM722NGd1a498Hidh5KxazDzyAvaE65ve2xuC2Rm8kff68GYPMwnLsnNJerJhrQ0zsaI6/bj/H8QeJ+NTTpt7nRKYVoqi8Ch1aC7Hm1dGhuaa/PyllvQXamWth/904RKUXwdG48fsPy7LY4/ccP1yMgJm2Mg7M6sjpPet9pGUky7y9W5yW7SJPG5wKTsbW68+wYWTbNx6PyyrGyaBkTOvSGgYNZLqlCcMwWD3EEQN/v41fr0Zh3QjnRp8fm1WEwrKqd+JX9irmOir4vK8tfrwYgUthqRjgbMTJfkOT8vDp4WAk5pZggJMh5vS0QruGdGtFoJ25Nk7M74qpe+5j/C5/7Pi4PXrailZBBgAhiXlYcTIUEWmFGNzWCGuGOUJf/e2cN+pK8lg1xBHjOpjhmzNhWHU6DEcDE7B+RFuREw918PKiKqN58yhhNWgQDnWdCX11TUzs2HRXGUBVI572+gi98wjsJ4vBKCpSgsCp4Y7OF5iZUWXSkSPivwYR8A5NxbWIDKwa7CC+rN3Jk+T7du0aTQr79WvwqV2tG09ENYqcHCWiXk9G9elDPw2xYAHJf3ToQAmTehjiYoQfLjzFvjtxTSbLAuNykJhTiiVer3VIKStTRU8tqalUcRYeTgGY33+nSqqaakpNFXl0sdbBpbBULB9gJ3QA6WlqASLSCvHdcCeaECsq0iS2d2+aJH333cuJf0UFdXadOkXv0YEDIlVzdrRsBVczLey+HYtJ4iajAfrMduygpKqQnaRV1YKa73UiJnY0x/oRzqIf38eHXn9lJVVdCXlsGdJlST9blFZWY4/fcyjJ84U6/wNic6CpLA8HUSbYamoSjlSGDBnNHXdzbZwJSUFKftnLAhYOYaursXz7Mig62QMzOgm/YVwc8Pz5By83NqmTOeKyi7HrVixa66oKrRzyTmjfnvyEt20DZsx4rz0xuCS7qAK6qgqSJTqjoynA7Ni4L3InKx0YaijhdHCy5MkyAAgLA44dI//S93wOyLIsvj4VhvIqAY7N7YIpewLwy5Uo/MVhoe6tqCy4m2uJFQjv3kYXCnI8XIvIQFdjFSqQs7R8Wbz4OmlpFKQ/f56SDI0VlLYwTgQloVrAcivBmJ9PRZtaWm89GcEVywbY41JYGtZ5P8He6VI+H+bNo59a5s+v6yf/OmvW0E9DXLxI69zi4pc/r2+flAQUFdG6PS/vRUyDZVkURsei8tFjMPn5MC4thIWgGnYevTBn0+dwM9MCY2oKpKTABIADAFZdHR9Nng5jTxtceZKOWaNXI17LCMr2NvB0NUc/JwM4GmmAAahgp1Z5x96e5ChfZcAAwM/vZRItMpKKG2rjJn/9BRw8CPbHHxGSwIOng4GQb/JrbN1KcYhRo8TbXkKU5PmY0qU1JnQ0x7lHKfjzZgwWHw3BL1eiMLeXFUa7m0JJno/EnBLsuh2LEW7GDXuGiYmVnhq6tdHBkfuJmN+7Tb2xjQfx1EXY3kLIY5uaks3MW8K1xv4oJDGv0WRZUXkVlp8IxfnHqejnaIBN41zFS7K2MKQyE2EYRolhGG+GYR4xDHOQaWDGxjDM3wzD3GMY5izDMHIMw3RgGCaJYRi/mh/hNKAYpsUZwpu1UsE4DzMcf5CIxJw39bu3XI+GPJ/BvN5W9Wz9drA1UMfkTuY4FBCPyLTCRp9b61HA9UVMHGZ3t4SjkQa+OROO/NJKifbFsiz2+j3H6D/voqpagBPzuuDPj9tzkiirxVpPDf8t6ArzViqYuT8Qp0XQhy8ur8K358Ixcvsd5JVU4q+pHtg22f2tJcpexdZAHUc+6YwtE9shs7AcY3fcFem11EvnzuRv9euvqPb1xextK7Ggl5VIHS0DnY0QLqeF5EkzaPIhTKKsllpzThUVqRqN5xZXYO3ZcLiYagonbfY61dXUhTdmDBmMNldfIHNzoGvXBhNlAE2eJnUyx7WIdCRkN+5t8O/DJKgpyqG/UyMdZMePU1XX1q1UVX7qFHWUvcYAZ0PEZZcgMr3xa92rnA5OhhyPweC2ryTl1dQoyLN+Pclv1J43CgpUcfTzz2T8KqLsCcMwmNfTCvHZJbgcnibStm8wbhz58jFMk+d1WWU1Fh4OwtHARCzybIPvR4qYKGNZ8ibr358qBQMDKWEqo1nAMAxWDXbA5E7m2OEbgz+uP2tym3vPs9HRUgi/MhkyZHxQvPQtk44UY25ZNfLkleFx+QTJdgvLjRv0u1aC6QNmxQB79HcywPrzT3D1Sfq7Hk7jrF9PwcR65mwfKtlF5dCR1K+struiiU4vPo/B8HbG8I3KfOGVJhHBwfSZPnwo+b7eMWcfpcDnaTq+7GcHNzMtzOlhhatP0sX38H6N7KJyhKXkiyzBWIuqohy6WOng2tN0sKtXk4fP7t0Nd/hbWFAxqZYW2RW82nXTgmFZFscCE9HRshV33VNVVbTOiooib28d0TsDmwN66opY3NcG1yMycD2imd8rXodhqHBWV5fObUfHusUBXl5UhLFoEfD118DPPyP9k4XY6RuDAb/dhovLPHSevh1f/XkV1x8loiK/EPZXT6OduTYVKuzbRwXVPj5AUhKY/Hzo/rkFX3jZ4uLiHlizcwUmTOsPZTVVbLkejcFb/NDjpxv47twTBMRmo7oxr2gNDaBbN+pI/Okn4MwZSpjV2qe0awcUFIAZOBC/710Oz9Ik0d+fyEhKis+b12hM5m0gz+dhlLspLn/eE7umtIe2qgK+PhWGHj/dwE7fGKw//wQ8hpK30mByJwsk55XCN6p+j8fAuFwYaijBVPvtWSKJgoWOCrRV5BGS2PCcODq9EMO3+uFiWCq+GmiPnVPayxJlNUirbOdjAEksy7oC0Abg9foTGIbpDkCOZdnOADQA9Kt57p8sy3av+YkU6mhr1gD793M19mbDp55twDAM/rgeXefvMZlFOB2cjKldWr+TpMerfNHXFmqKclh//kmjBozBibnQUJKDlTTbtIVEjs/DxtEuyCoqx8ZLEWLvJ7+kEnMPPsR33k/Qy1YPFxb3QHsL6XjrGGgo4fi8LvBorY3Pj4Xgr1uxTW5zIzID/X69hf134/BxJwtc/V9PeDmKWV3CEQzDYJirMa583gvtLei1bLvxTGjzznqRkwO7eDEWrjqEn8Z8iQmdLKhi69atpre9cAEf8fOgKM/HX32nA1ZiJp+joykBEhws3vZNsOHCU+SXVuLHUS6i+0hkZwODBgE//gjMmQP4+gImEvqdvWMmd7IAn2FwwD+uwecUl1fhwuNUDHExatxLwdOTPvdFi2iReOsWJe1eo5+jIRgGuPhYuERUtYDFmZAU9LLVqxu44PHII+6TT6iCs18/qqYFSPrxyy/Frqjt52SI1joq2OkbI9l3qpa9e6kDTiCo9+GCskpM23sfl8PTsWaoI5b0E77r7gUlJXSc0aOBgIC35v8nQ3gYhsG64c4Y094Um69GYdetmAafm5pfivjsEnSylPnMyZAhoy72RupQkudJzbcsMacEOzuNhkJpMXWJC8vYsSSv1EQnzYcAj8fgt/Ht4GKiic+OBONxUv67HlLDaGtTRf1bkjN6H8gqqpDcr+zpUwomC+FbO7KdCaoELLxDUyU7JkBrFR4POHtW8n29Q7KKyrH2bDhczbQws6Y7c0Z3S7RSVcAvV4QLbTWF37MssCzEUpuppa+DPkrjEsjOYO7cposFLC1pjWRgQAVuN2+Kfez3hXuxOYjPLsEELrvK/P1Jim3HDuCjj7jb7ztgapfWsNZTxTrvpyivqn7Xw+GckooqnApOwpQ9AejywzX8cDECqop8rBvhjPsr+2LnFA/0dzaCgoZaXeuAfv2AiRNJKcbE5A2ZTXMdFczuYYXj87og8Ou+2Di6LWwN1PHPvXiM33UPHTf44Oj9BPEG7ekJRETg8dJv4ZQRi0HThpCSjaiMH0+ximYCj8egn5MhTi/oikOzO8HWQA0/XIzA5fB0zOtlDWMpqBUAgJejAfTUFXHoXv2fx8O4HHi01m62stUMw8DVTKvBQo2zj1IwfNsd5JdW4tDszpjby7rZvpZ3gbSSZZ4Artb8+zqA+u4E6QB+f20c2gBGMwxzn2GYkw11pL3B/v0t8oZtpKmMSR3NcTIoGXFZL9uDt1yLhqIcH3N6vruuslq0VRXweV9b3I7OwvWI+jPuABCckAc3c+1mU2ne1lQTM7tZ4nBAAu6/YsIpLEEJuRi05TZuRJIs3l9TPaClIl1TYg0lefw9syMGtzXChgtPsd77CQT1VJ5kF5Vj8dFgzNgXCGUFPk7M64J1I5yh3owqBDRV6LUMdzPGz5cjsfLUY1RV1x+QFwb/mGxcypND/wle1FW2aRN1CU2fTt5Y9XHkCDB8OFTWrEZvOz1cCk+r9/0UCi0t0pceM6auJjYH+EVn4cTDJMztZdWk1nC9bN5M18dduyhJ0wK6cA01lTCwrRGOPUhEcXlVvc+5GJaGkopqjGnfhCmpri5Vfn35JWn2t6nfA1JPXREdLFoJ3bUVEJuNtIIyjHSvJzHJ49Eiac4cOra3N/1dwskJn8dgVg8rPErKr2MuLDY8HklVbNv2xkOZheWYsPMeHsbn4vcJbpjRTUS5pmfPgNJSSlDevk3SOzIpvmYLj8dg42gXDHExwvcXIhpMVAfE0nnX2er9rJSVIUOG9JDn8+BiqoWgBG7nSbUk5pYgQt8SRZ5eJKdcWirchmpqFPyVBQgAAMoKfPw1zQOtVBUw6+9ABMZxMJ+QFjweqSfs2AHkNONxviWyi8qhoyrhPN/ZGVi4kDovmsDeUAP2hur4T1KlEIA6bLp3f++TZWvOhqO4vBqbxri8UFpQU5TDgt7WuB2dhXs1vq6S4BuVCW0VeTibiO9l7ulggHR1XZzaepw6VITB1JSKLt3dhfZUfp85FpgAdSU5DOTItgMA0KMHJaRnzeJun+8IBTke1gx1wvOsYuy7E/euh8MJCdkl+PtuHKbvu492313FF8ce4XlWMT79qA1ufNkb/y3ohimdLaCtyk3cT1dNEeM7mGPv9A4I+sYL2ya5w8ZADSv+e4w1Z8LEi48pKOBk99Hov3AvBMtXkN8aQDGqbCGuP3Z2wNGjjXu7vyMYhkG3Nro4NLszTi/shi/72WJeL2upHU+ez8OEDma4HpmBpNy6ikbJeaVIyf8/e/cdHkW5BXD4N5tNIZWE9AYk1BAIvXcB6QIiCIgoAipi715FvPZ2FRWxoKIiKEpVKUoH6RB6gEAoCTUVSAKpc//4CEXSd5PNJud9Hh5gMzM5u5kkO3O+c84VWha3BaOFNA2qTvT5VFJvuGeWmZ3LlMX7eWxOJGF+rvz5WCfahcq1+7+VVbKsBpC3FO0icMsSY13Xo3Vd36pp2mAgF/gLOAK8out6a8AP6FKsz5aWVmkHw0/sFoqtjcbUlaq6LPrcJRbvPs2Y9rXwNLXNgpmMbleTEC8n3vwziszsW3+gp2Zkc+jcJZqZMp+qDDzVqx4B1avx4vw9xV4Nk5ur89W6owz7YhOaBr8+1J5xnULKLQNvb7ThkxHNGNOuJjM2HOOJX3Zde811XWfejjh6/G8tS/ae4YkedfnzsY5lVu1mKnujDR8Na8oj3UKZszWWcT9sLzDxURhd1/loxWF8XR2u9xN/8UX1Z/Zs9Qt/xoybq2O++EINb+3QAb79lj7hfpy7mEFkISXKhfLyUq0UTp5UCToztWTcHJPIk3N3EeLpxKMFDBbNl66r5B2o4eebN1eo1UHmcF/7mly6kl3gBfpvO2KpVcOxeD2kfX1V+8N8Kspu1Dvcl4NnL3EsIa3Q7QDmR57C2d5Ij4J6heclzE6ehBdeKDrGYrqrRSA1nOz4qhjVp0UaMwb69FHxxVw/3snEdIZ+sZFjCWnMGNOSO5qWsFJx0SJVifn88+r/Xl5yk9IK2Bg0PhrelJ5hPkxetJ+522Jv2WZzTCKuDkYa+lXQVq9CCItqHuzOgdMXuJJl/lXosUkqOWZ44QW1UKo4XUeOH4cpU+CUGW72VyLeLg58e18rbG0M3PXFJiYv2nfTjZYK5dAhmDQJXnrJ0pFYlK7rJKRl4uli4k3cO+9U1UbFNKR5ALtjU4iJTzXt8wIMGAB79sCJE6YfywKW7TvDn3vO8HiPutT1cbnpY/e0rYmPqz0fLD9kUvcHXddZH51Ax7pepZ9PDARcOE8DXxd+1n1K1p7fz08lzCIi1P8Plr5LT0V2IT2LpfvOMqhpQOEdSorrzz9h4UL17wIWZlqjzvW86Bnmw6crozl38YqlwymxjOwcNkQn8PofB+j+4Ro6v7+aVxfv52RiOiPbBPPLhLase7YbT/Wqb75WnAVwtjfSr4kfP41ry7iOtfl+0wnGfLeVlPTMEh8rMjaF2nX8MbzztpqVDmoeZGioSo4XtJho3TqVzLUCTYOqM6l73RKNXymNu1sHowE/b735unf71YVELWtVzHuteSKCqqPrsCdOLVQ7e+EKI77ezMyNxxnboTZzJrTFx9Wy3eoqqrJKliUAeUtd3K7+/xaapg0EHgMG6LqeDRwHVlz98HHAu4D9Jmiatl3TtO3x8fGVOlnm7eLAve1qsXDXKY6cv8TUldE42laMqrI8tjYGXukXRkxCWr6rzffEpqDr0Cy4YiXLHO2MvDk4nKPxaXy+uuC2UnmS0zIZ98N23lpykB4NffjzsU40tUAC0MagMWVgI57rXZ/Fu08zduY2Dpy+yL3fbuXpX3cT4uXMksc68USPetgby/aXh6kMBo1nb2/AW4Mbsz46geFfbeJ8Cd9obTyayLbjyUzsFnr9l6WjoxqYu2sXNG6sEkV5CYl331VDYfv1U1Uzrq50b+iNnY2h2C328tWunapoW7QIPvyw9McBsnJyeW/ZQUZ8vRlneyOf39O8+G8EUlJUL/R27eDSJVVJVgkHnzcPdqdxgBvfbzx+y0VnbFI6m2OSGNoi0KyJ7NvD1QqrZfsKP08uZ+awbN9Z+oT7Fv510zQIMmNrD9RMt3vb1WLVwfMcLsF8tXxpmqpGNBrVCsjcXA6dvcSdX2zkwuUsZo9vQ9f6+f6azl9OjprTNmiQarf4zDOmxSfKna2Ngc9GNqNLPS+en7+HRbtuvsG85VgSrWt7mHQDRwhReTULrk5Wjs6+U+Zv7xebnI67oy2OPbqpIfd33130TsuWqRtIxa1Cq0Lq+7rw15Odua99LX7cfIJe/1vL6kK6iFhMWJhqpf3VV2ruaRWVmpFNZnYunqZUluXmQkK+t20KNDAiAE2DhbvMMDtu4EDVrcMKEzDJaZm8vHA/jfxd871P42Brw6Tuddl+Ipm1hwvoelIMUWcuEX8pg851PUsfbGQk1K3L43Eb2XEiueQ34/Ourb75Rl1n//Zb6WOpoBbtPkVGdu71hbim2L1btbV7+211LVTJvNIvjKxcnXeWWsf37emUy8zecpLxP2yn2X//5p5vtvDj5hMEuTsyZUAYa57pyqpnuvLqgEa0CalR7p2xbAwaL/cP4/2hTdh2LJlB0/7hyPniX9NnZOcQdfrirfdeH3hAVe8+/7xaTP799zefj7quWrKOGWOmZ1I5BFSvRrf63vy8LZasGyr9th1PwtneSANfl0L2trymgeo82BWbwsYjCfT7ZD0Hz1zks5HNmDwgDNuSjnipQsrqlVmJmkEGqiXj6n9voGmaL/As0F/X9bzv/qeAuzVNMwDhwL78Dq7r+le6rrfUdb2ll5cXXLlSaZNlAA92DqGarQ3P/raHP/ee4f4Oqu91RdKtgTdd6nkxdWU0SWk3v+HKm03QLKjilah2re/NHU39+XzNEaILubG87XgSfT9Zz4boBF4b2Ijp9zTHrZrl2hpqmsbErnV4f2gTNsUk0veT9USeTOH1Oxrx64PtblnNVtGNbBPMjHtbEhOfxuDPNxb6tbiRrut89Pe/qspuFBamWhB+95365Z+ZqZJZI0bA/PnXWoy4OtjSsa4nS/edNW3W02OPqdkXCxaU+s3wsYQ0hk7fyOdrjjKsRRB/PNqRBr7FXPG3eTM0bapWrj34YKX+uahpGve1r8WR86n8c+TmlgLzdsahaTCkeREtGEsooHo1IgLdWLav8NkMK6LOkZqRzeBmlpkNN7pdTRxsDeapLgsKUsnfNWs4v+RvRn+zBYMGvz7YjmbBxfiZnvf9tGKF6tv+xhswdqxqvVhEJZ+omOyNNnw5ugVta9fgqbm7r30/nL1whWMJadKCUQhRoOZXf2+UxdyyuOTLBLo7qhu548YVr03YqlWqtVho2bXxsWZO9kamDGzEbw+1x8neyP0zt/H4z5EkpmZYOrSbvfaa6hLw8MOV8mZ0cSSmqutvk2aWHT2qqv1nzSr2Lr5uDnQI9WRh5CnT5+XWq6c6Y9x+u2nHsYDX/zhASnom7w1tUuDNx+Etgwh0r8aHfx0u9Wu1Llol2ko9rywrS70Pr1GDgHuHkZOrlz55d9dd0KaNSgT99FPpjlEB6brOnK2xhAe4mtTqEoAzZ6B/f/X7aOFCsKnYC5lLI7iGIxM6hbAg8tS1apuKJCsnly0xibyz9CC9P15H+3dW8dKCvRw4fZEhzQP4ZkxLdk3uyfdjW3Nfh9rUKuMKsuK6q2UQcya0ITUjh8HTNhZ7scr+0xfJzMm9tatXeLga/bB6tfp9ed998Oyz1z++cqVaqDBpkvmeRCUxqm0wCakZ/H3g3LXHth9PpllwdYwVPNnk7mRHrRqO/LDxBPd8swV3JzsWTepA/yb+lg6twiurr+xPQICmaXuAJOCopmkf/GubMahWi8s1TdugadpY4DPgfmALsEDX9QNFfqbcXHVD2MW6kgMlUcPZnvs71CLyZArOdkbGdSrhbJhy8nK/hqRn5vC/v28eXht5MoVQLyfcHCvOzKwbvdI/DCd7Iy/M33vLzKrcXJ1pq49w91ebsTMamPdwe8a0r1VhBh/e1TKIb+9rxag2wfz9VGdGt6tVYebClVS3Bt7MfbAdmTm5DJm+kU1Hi+6p/M+RRLafSOaRbqEFV9FpmnozEBoKdnawfDn8+CPY3nw+9g735VTKZfaastpZ0+Dbb9XNlxK+GdZ1nbnbYun3yXqOJ6YzfVRz3h3aBCd7Y9E75+aqirmOHVUMGzbAc8+pVn+VWP8IPzyd7Zi58di1x3JzdebtjKNjHc8yGfZ6e7gvu+MucCql4FXoCyJP4efmYLGkgYeTHcNbBrFo1ynOXjBDS4wHHuDiuo2MOGTPlawcfhjbpuCEfHKySkRPnKhuevzwg3q8dm016HjePNUW1UHK/a2Zg60NM8a0JCLQjUfnRLL64Hm2HFM/s9vUlmSZECJ/Xi72BHlUI7IM5pbFJaUT5HHD7/1lywpvjZ2bq24ade8urYCL0KKmO3881pHHb6vLkr1n6PnROvMkR8zF1VUt7NmxQ1WYVUGJaSqBWcOUMQ0Hrt56qVuC1u/AoGYBnExKN08SPO/6LLf0s6zL26qD55gfeYqJXUNp5F9wcsXOaOCJHvXYe+pC8WYgZ2Tc8vNr3eF4Gvi6lL5t1nvvqc4r06cTHl7s1iaFAAAgAElEQVQbT2c7VkSVsmLU1VX9nO3SBUaPVpVmlcC+UxeJOnOR4a1MXNSXnq6qJVNSVJLCz4yzzyqYid1C8XV1YMrv+8kp7Qx4M7mSlcOOE0l8vS6GB3/cTvPX/2b4V5uZsT4Gd0c7XurbgL+f7MyG57vxxqDG3NbQB0e7YtxvsYAWNT1YPKkDwTUcGfv9Nr5ad7TI37u7rr6/alpQoULXrrBli5oX/tBD6rGjR9WiE09P1aFI3KRLPW8Cqlfjpy2qRfCFy1kcOneJlhV03M2/NQt25+zFK/Rt7MeiRzpQx7vy5k7MqUzupOq6nqHren9d15vouj5a1/Vjuq4/869t3tV1vY6u6x2v/vlW1/Uzuq531XW9la7rrxbvGRggNRWeeqosnkqFMaFTKJ7O9jzcLZTqjhWrqixPXR8XRretyewtJzl0VlUG6bpOZGxK8SoQLMTT2Z6X+4Wx40QyP209ee3xhNQM7pu5jfeXH6J3uC9/PNqRxoEmri4qA13qefHm4Mb4uZk/MVDewgPcWDCxPT6uDtz77ZZbWnzdKG9WmZ+bA8NK0iLBxSXfRFavMB+MBo2lRbTYK5Kzs2p9mJys5oVlFz3j4UJ6FpNmR/LcvD1EBFZn2ROd6NO4BG+oc3NVL/QhQ1RrjTZtTHgC1sPeaMPI1sGsPHieE4lqjtiWY0nEJl1maAvzVpXl6d1ItWJcXsB5kpiawdrD8Qxs6m/RxPW4TiHk5Op8d0MisbQuZ+Vy395cYpMvM6udC/V9nK9/MO8Ne3o6tGqlBrTfeadKSNerBz5XZ7aFhqpVp0OGyE3JSsLJ3sjMsa1p4OvKg7N28N0/x3GxNxLmL/PKhBAFax7szs6TyWZNtOTm6sQlXybI3fH6g3Fxqs3QypX577R/v2o5162b2eKozOyNNjzZsx5/PNqJYA9HnvhlF2NnbuN0IYuHytXdd6uuCmFhlo7EIhLyKstM6T6TN6umYcMS7dY73BcHWwMLCpgjXCInTqgWYfPmmX6scnDxShYvzd9HPR9nHule9Cyqwc0CCPVy4sO/DhecVDh0CEaOVB1Qhgy59l47PTOb7ceTS19Vtn8//Pe/qhJs0CAMBo1u9b1Ze+j8Te3FSsTZWV2D9uqlvv+OHCndcSqQn7edxN5oYGCEiZUXc+bAzp3q77wZb5WUo52Rl/o1ZN+pi8zdfutM47J09sIVluw9wxt/HGDw5//QZMpf3Dl9E28uiSLqzCX6hPvyxT3NiZzckzkT2jKhcyh1fVwqzOL3ovhXr8avD7Wjb7gfby05yNO/7i507mtkbAp+bg74uhWSUNc0lRSrV0/9/7XX1GLrCRNkQWs+bAwaI1oH8c+RRGLiU6++h4VWtSruPe4bPd2rHl+NbsGnI5oVbyG+AMquskyYmZujLZtf7M7DXSp2m5AnetTFxcGW1/84gK7rnExKJykts8LNK/u3O5sH0KFODd5bepCzF66wOSaRvlPXszkmkTcGhfPZiGa4OFTMyrjKJtDdkXkPtad5sDuP/7yLaauP5HtDZcORBHacSGZitzpmmc1W3dGOdqE1WLr3jHlu4Pz1F7z+ukqYFWJzTCJ9pq5j+f6zPN+7AbPGtSl+4nPFCjh3Ts2UWrJErRCqXrG/18xtVNua2GgaP2xSK31+2xGHi72RXmG+ZfL5Qrycqe/jwrICVoT+secMObm6xVow5gnycKRPYz9mbz7JpStZpT5Odk4uj86JJDI2he/DcmnSt5O60H73XejZE+65R23o6Khubrz6qnqznZSkVlH27m2mZyQqIlcHW34Y25oQTyd2xabIvDIhRJGaB7tz7mIGp81R+XzV+UsZZObkEuhxQ7Js9Gi1kv/dd/PfKTpa/e6SZFmJ1Pd1Yd7D7XmlfxibY5Lo+b+1/LDp+C3dOcqdpsEXX6gqF12HGDO0orYieW0YPU2tLAsIUBVDJeB89X33H3vOkJltYkVYQAAkJsLixaYd51+W7TvD/tPmn5X49pIozl+6wvtDI4p1PWpj0HiqZ32iz6eyePe/kovHjqlq2LAwNTbg3nvV+axpoOtsOXyOzJxcOtctZbLs0CHw94dPP7320G0Nfbh4RSXhSq1aNRXv0qVQp+iEobnl5OolmulUmMuZOSzedZp+jf1MH7kxdqyqdu3f3yyxVXQDmvjRupYH7y8/xIX00l97FiYrJ5fdsSl8988xJs3eSYd3VtH27ZVM/GknP2w+gdGgcX+HWnw5ugXb/tODdc91472hEfQO97Pqe3mOdkY+G9mMJ3vUY/7OU4z4ejPnL+b/HmpXbDJN/92CsSiffqq6I73wghmirZyGtQrCaNCYs/UkO44nY2PQaFrB73HnCXR3pFcjX6tJEFcU1p8sy8iAUaPUqo1KzmhjqPAneHVHO57sUZcNRxJYGXX+WpuVijiv7EaapvHmoMZk5uQycsZmRn69GWd7IwsnduCetjUr/Ote2bg52vLDA625o6k/7y8/xEsL9pF9w4q3vFll/m4ODGtpvgqiPuF+HE9M5+BZM7zhHj4cxo9Xw3z/+OOWD2fl5PL+8oOM+Hoz9rY2zJ/Ynoe7hhbvRnNWlnoz07OnSlyAWtlXBc9TH1cH+jT2Y+62WM5fusLSfWfoH+FHNbuy6wnfO9yXbceTiL9068yO+ZGnaOjnWvw5c2Xowc4hXMrIZs4NFbMloes6ryzax4qoc7w2sBHt7u6jLtqnTFHn37lzN7fqmTVLJcs6dLilzamovNyd7PjxgTZ0quvJiNYyh04IUbhrc8tOmG9uWWxyOgBB7jcsNrK3hyeeUAuLduy4dachQ1QXgJo1zRZHVWFj0HigY23+erIzzWu6M3nRfoZ9uYkj51MtHZry2WdqPstff1k6knKTcHWOnElzzQ8cKHVl3uBmAaSkZ7HmUClb+uUxGqFfP1WtVIzuHMVxIjGNh2btZNC0f/hq3dGSJ3YLWES5ITqBOVtjGd85hIgS3JzuE+5LmJ8rH/0dfXNFV2SkWvj4xBMqcTZzpvo3wIIFNOrXlfZnomhZ2mqGIUPg8GE1l+6qTnU9sbMxsDLqXCE7FoO9vbouBZU0++QT045XAu8sjaLH/9bx9NzdpGaYds4s2XuGSxnZ+c9CL66ff4a9e9V1edOmJsVjTTRN49WBYaSkZ/LRisNmO+6240m8s/Qgw77YROMpy7lj2j+89vsBdpxIpmlwdV7pH8bCRzqwb8rt/PpQe17s25DbG/ni5WLCwoEKSNM0Hu9Rl+mjmnPwzCUGfvYPe+NuXgCQkJpBbNLlkhcquLnB/fdX6tFGpvJ2ceD2Rr78uiOODUcSaOTvWmHbdwrzsP5kWVYWzJ6thsGKCmFU25rU8XbmzSVRbDmWiKOdDfVubNtVQdXydOLJnvWIiU9jYIQ/ix/tKO2kLMjeaMNHw5oysWsoc7aeZPwP20m7+gZ4fXQCO0+mmK2qLE+vRj4YNExvxZjnk0+gWTO1uvmGhP7xhDSGTt/ItNVHGdYiiD8e7UiTwGK+qTl2DDp1UiulH3wQ3n/fPLFasfva1+JSRjYTZ+0kPTOnzFow5ukd7ouuc9OQV4CY+FR2x6YwuFnFGJjaJLA67UJq8O2G46Va6Tt1ZTRztsbySLdQ7m1XS7U9/uUX+O03NbB6zx6VOBNVnpeLPT8+0IYeYT6WDkUIUcE18HPBwdZgnvlGV8UmXU2W3VhZBup9kqurmtOTH7uK2dreWgR5OPLD2NZ8cFcE0edT6Tt1PZ+tii59SzdzGT5ctZcaMAAWLrRsLOUkMTUDVwcjdkYTbu88+SQ88kipdu1Y15MaTnbmacU4YIBKZG/caPqxgJ+3xWLQoFNdL95acpAx320tsCrjFgcPgq+vak3500/XHk7LyOaF+XsI8XTiyR71ShSPwaDxzO31yDhxkmPD74O33lIfGDxYXed9+CF4e9+8k7Mz+sVLzP7hWRwmPqQ6OBRXdLRKvOn6LYvZnOyNtA2twaqDZryXNmsWPP44fPyx+Y5ZgB0nkpmx4RjhAa4siIyj79T17DBhIcYv22Kp7elE69qlnEW0erW67q+i10eN/N0Y2SaYHzefuDaWpbQOnr3Ifd9t5a4vNvHNhhgycnIZ2bomn41sxsYXurPpxduYNrI5D3SsTdOg6qb97LMifRr78dvD7bAxaNz15UZ+33362seKnFcmTDKqTTAp6Vnsik2xmnllovSs/ydK3vBX54qfjKkqbG0MvNyvIccS0vhlWywRgdUx2ljHqfZg5xBWPt2Fj4Y3xVn6uVqcwaDxXO8GvDk4nLWH4xn+1SbOX7zCRyvyqspMWPWVD09ne1rV8mDp3jPmOaCDg0osALzzDrquM3d7LAuHPULtDSv47jZf3r2zcfF7B69bp1aoHTwIc+eqdjOOjkXvV8k1D65Ok0A3tp9IJsTT6dqq9bLSwNeFWjUcWbrv5vNk4a7TaBoMjLBsC8YbTegSwtmLV1h8wxvp4pi95SQfr4hmaItAnulV//oHvLzUTDLfsmlzKYQQonKztTHQJLA6O6/e1DGH2CQ1Nyug+r/aWLu5wRtv3NoSeMcOaN4cdu0yWwxVlaZpDG0RyIqnutCzkQ8f/HWYAZ9uYE+c+b6+JebtrW5aN2sGQ4eqhbWVXEJaJp6mVlKMGgV33FGqXW1tDAyI8Gdl1HkuXDaxBdvtt6tEthlaMWZm5/Lr9li6N/DhmzEteXtIY7YdT6L31PWsOlhENdXp0yoWTYPAQLVoDODYMQ73HUqjLSv5oE8IDrYlXLh59izdpr/F+q8mELJgNtmJVxNfmlbg++u4Vh3pdv9n7Ll7PHz3HTRoAPPnF/25cnPhgQdUhVpCQr6b9GjoTUxCGjHxZqoMnTlTVbE9+WSZJsyuZOXw7G+78Xerxs8T2vHLg+3I1XWGfbmJj1ccvqkrTXEcjU9l6/EkhrcKKl1XoUOH1POuVw+++abk+1cST/esj7O9kdd+31+q0RanUy7zzK+76TN1PTtPJPNinwbsfrUXix7pwOQBYfRv4o//v3/XVzGN/N1YNKkD4f5uPDonkg//OkRurs6u2BRsDBqNA9wsHWKl1C60BiGeToD1zCsTpWcdGYzC5CXLnJwsG4e4Sdf63nSr70WuToWfV3YjTdMI9XKWtosVzKg2NflmTCti4tO4/eN1RJ5M4ZHudcpkBVHfxn5En081W+9zQkIgMpJLTz7LpNmRvP3Deh5dO4uPf3mNbr1aqnka/furlhVQYKsPABo1gh49VJuOu+4yT3yVgKZp3Ne+FgB3tggs8+9fTdO4PdyXTUcTr/Vk13WdhZGn6BDqWfhA3XLWtZ4X9X1c+HpdTLEvWP4+cI6XF+6la30v3h7SWH4eCiGEMKvmwe4cOH2h0CH1JRGXnI6Pq33+N60ffVS1F7rRypXqvZQs/DAbLxd7po1szlejW5CcnsmQzzdaNmHm7g5//w0dO6o5UCdOWC6WcpCYmoGnkwnJsjNnVPLYhNaHg5sFkJmTa/qiQxcXeO016N7dtOMAK6POkZCaycg2KgEyonUwfzzaER9XB8bO3M6Uxfvz/zl04QL07asquJYsUefSiBEAHFqzjZB/VvDlgrdo3qKeahv55Zdw8WLRAc2cCSEhaNOmkTxoKF0nfMX3g4uu5lt3OIF0u2o4Tv1QJftDQuBKMarjpk+H9evho49uar94o+4NVBXbyigzVZfZ2qpWhHfeWaYJs49WHCYmPo1372yCs72RVrU8WPJ4JwZG+PPximiGfbmJk4nphR8kNxfOngVdZ+62WIwGjSHNS7HoMSFBnQe2tmr8QhWbIX4jdyc7nulVj41HE1lWgm49Fy5n8c7Sg3T7YA2Ld51mXMfarHuuGw92CZV2d/nwdLbnp/FtGNYykE9XHeGhWTvYFJNIA1+XMh1HUZVpmsZ9HWphbzTQspZUllV2kiwTZebl/mH4uNpfewMmhCm6NfDmlwntMNoYCHSvxl0tzFtVluf2RurGydK9ZmrFCGzVXbl9zUWW7z/LhCFt1MXUpk1qmGrv3nD8+PV2Grt3q9WLgwap1dBz56qbPFlZUKMGzJsHtWubLbbKYkCEP68NbMSYq0mzstYn3I/sXJ0VV3v87zyZzMmkdAY1qzhVZaDe1E3oHMKhc5dYczi+yO13nEhi0uydNA5w4/NRzbG1kqpgIYQQ1qN5cHWycnT2nbpQ9MbFEJucTqB7IZX2aWkwdaq6KQqwapWazSTJMrPr1ciXZY93xsPJjhfm7bVsS0YXF5Xo+PPPSj+bLjE1kxrOJrQV/flnVYmXUvoEZ5NAN0K8nJhvjlaML7ygklUmmr31JP5uDnSpd/1+RB1vFxZMbM/YDrWZufE4g6b9Q/S5fy2S1DS1oHH+fFWFetXlzBweTPDijlfnc+WvFTBxoqoomjgRMjPVRlu2qGR83iK1pCQ15xfUwsc774SoKHx+/YmaLcL4fPWRa6MGCrLucDz+bg6EejlDRIRqUXk1ecdnn8Hrr0PGv2YpHz8Ozz8PvXqphHEBAt0daeDrwsqiKu1KwtYW5sxRz/XQocIXg5bCrtgUvl4Xw4jWQXSs63ntcVcHWz4a3pSpdzcl+lwqfT9Zz7wdcfkvGDxwQM1Z9vMja/lfzNsZxzDPbLz37CheIvJG77wDcXGwaJFcpwMjWgfTwNeFN/6M4nJm4YtiMrJzmLE+hi7vr+aLtUfp29iPlU934T/9wqjuKK2SC2NvtOHdO5swuX8YK6LOqTluJZifKEpudNuabHyhe6WbiSduVTnugnl7SxvGCijUy5ktL/WQrLswm8aBbqx4sgsLH+lQZn2pfd0caFHT3Wxzy9YcOs89M7Zgb2vDvIfb83DXUGycHKFtW5g0Sa0w3LdPtT4BNdi6Wzd1YTF5spq7sGQJHDlilngqK1sbA2Pa1yq39qlNAtzwc3Ng2X51niyIPIWDrYHbG1W8mU0DIvzxdXXgy7VHC93uyPlUHvh+O35uDnx7XytZxSeEEKJMNK+p2tdsN2G2zI1iky4T5F5IW6ZTp1SFwyefqBvaGzao91qiTLg72fHfO8I5cOYiM9Yfs2wwjo7Qs6f69+LFaj6UmW/cVwSJaSYmyw4cAE9P9aeUNE1jcNMAth5LIi65iIqe4oiOhm3bSr37ycR01kcnMLxVMDaGm7skONjaMHlAGN/d14r4Sxn0/3QDszafQM/JUYkSV1d1/ZV37lz10YrDHE9M5627muPQ8zb43/9UnEeOXH/tXnlFJdhq1lTXd7Vrw4svqo+1agU//gh16wLwdK/6JKZlMnPj8QKfR3ZOLv8cTaBzPa/r3R4MBpXQA5WYmzxZtepfu1Y9puswfrza5quvrm9bgNsaerPtePK1jhlmkVdhNm2a+vyXzNO1JSM7h2d/3Y2PqwMv9m2Y7zZ3NA1g6ROdCPNz5elfd/PonMjrzy0zU1UuNm2qvnavvcZat1okpGYy7vg/qhrV1RXatYNnnlEJ07xEaEHeeku1fm3XzizP0doZbQxMGdiIUymX+XJd/tefubk6i3ad4rYP1/LGn1E0DnDjj0c78tHwprfOHxUF0jSNsR1rM/P+1gR7ONK3sZ+lQ6rUNE2jhrMkyqoC60+WeXiolTr+/paORAhRDtwcbfEs419QfcJ9OXDmIicS00w6zvroeCb8uIO6Ps4smNieiOKs9AkPVxdRUVFqdeeGDeoCtmH+FwPCMgwGjdsb+bLucDwp6Zn8secMPcN8cXGwLXrncmZnNPBAx9psjkkqsCXSuYtXGPPtVowGAz+MbSNvAoUQQpQZT2d7wgNcmbs9lpxc0xIXWTm5nLlwufCba/XqqVkyn3+uqsrS0szS4k0UrHe4L70b+fLxisMcSzDt/bTZ/P47/Oc/KnFRiRJm2Tm5JKdnUsOUNoxRUara0kR5HRYW7SrZrNx8DRsGTz1V6t1/3nYSgwbDWgUWuE23Bt4sfaITrWt78PLCffzd/16yu3aD9PRbEkyRJ5OZsT6GkW2CaV/nhqSipt1cTTRrFnz7LbRooRJut92mkvX5aB7szm0NvPly7dECZ73tik3h0pVsOtfLv40i33yj2vlnZEDXrjB2LCQmwmOPqTaMxaiq7N7Ah5xcnTWHzdSKMY/RqBJ7p06pa9yPPjL5kJ+sjCb6fCpvD2mMayHXXYHujsyZ0JZnb6/Psn1n6TN1HZuOJqrxB1OmqJEGUVEweTKzDl7A19WB4P88DQsXqq+X0aiq9u655/q5MGuWSv7ltSydNUu1YLSzk0TZv7QNqUH/Jn5MX3P0luT5P0cSGDhtA4//vAsXB1t+GNuaHx9oQ7jM2iq1zvW8WPdcNzrUKf2CByHEddafLBNCCDO71orRhOqyjUcSGPf9dkI8nZj1QJvStRFwdVXtIWrUKHUcouz0DvclIzuXKYv3k5KexZAK1oLxRne3DsLF3siX62Ju+djFK1mM+XYrKemZzLy/FcE1ZDWfEEKIsvVg51Bi4tP4a79plfxnUq6Qq0NQYW0YQbUju3ABfvhBtQbr0sWkzyuK9todjbAzGnhx/p5iz00tU19+CQ89BO++q2bZ5VqwRaQZJadnoevgWdrKMl0328K8IA9HWtVyZ0HkKdO/5gMHqnaDCQkl3jUrJ5e52+Po3sAbP7dCqk4BbxcHvr+/NT+nbqTXstks0HzYePrmBG9Gdg7P/rZHVTP1aVD4J/f2Vi30FyyA5GRVmdS4cYGbP9WrHhevZPN1Pu/RQbVgNGjQIbSQm+C9e6tOJS+8AD/9pDqUDBigEj3F0DSoOjWc7Fh10MzJsjze3tC6tUp+mpAw2xt3gS/WxjC0RSBd6xc96sPGoPFItzosGBOBo0Fn5IzN/NppKFkLF6nXycuL0ymXWXc4nrtaBmL08YY77lA/I9avV6MTtm9XVXIAs2erzjDNmqm5iKNHq21Fvl7q2xBNg7eWRAEQdeYiY77dyqgZW0hOy+J/wyL489GOBSeChRDCQqw/WZaQoFaFCCGEmQR5ONIk0K3UybItMYk88P12atZw5KdxbXB3kn7blVGrWh7UcLJj4a7T1HCyu6lnfkXj4mDLyLbBLN175qZh1xnZOUz4YTtHzqfyxegWsqJPCCFEuejb2I+aNRz5fM1Rk26qx15dsR7oUfgNcVq1Uq0X161TNzxlIVKZ83F14KW+Ddkck8Tc7bGWDkdVuHz+uWqtNm0aPPAA5BQ+T8caJKSqWVWl7gpw/rxK6pihsgxUddmR86nsP33RtAMNGKASmkuWlHjXlVHnSEjNYETr4GJtb5j7C22nvcWFfnfw5eBHGfXNVt5ffvDazL1PVx7hyNVqJnN3kWjk70a/Jn58+8+xa1/LG62NTqBpUHXcHIv4vI6O8PbbalZZhw4lisHGoNGtgTdrDsWTXRZzBm1t1c/du+4qdcIsMzuXZ3/bTQ0nO17pV4JzdcUKGvfuyJKsrQxvGcSzaQEMPunO0fhUAH7bEUeuDsNa5jMP3c7u5u+LP/9Ur+/s2TBmjGp1+frrJX4uVYV/9Wo80rUOS/aeZezMbfT9ZD2RJ5N5qW8DVj7dhSHNAzEYCm8RKoQQlmD9ybL0dFixwtJRCCEqmd7hvuyOTeFUyuUS7bf9eBL3z9yGf3UHfhrXVtrZVWI2Bo1eV2eUDYjwx9amYv9KHduhNjYGjRkb1MrV3Fydp+buZnNMEh/cFUGnurKqTwghRPmwMWg82DmUvacusOFIyStH8sQmqWRZkZVloKrLatdWLfxFuRjeMog2tT14888ozl+6YulwVDu1995TM4tcXFQCzcolpqp5SjVKuzjP1RWWLVMVNWbQr7EfdjYG5u88ZdqBmjdXozYWLy7xrrO3xuLn5lCs6iNWr4Z774XOnXH77WcWPd6FYS2CmLb6KHd9sYll+84wfe3RYlczlcaTPepxJSuH6Wtunu+UnJbJnriUklXe+JVuZlGPht5cuJxltlmSt7C1VdVceQmzn34q0e7TVh/h4NlLvDW4cdGJQ1AJ4LFj1dw5OzvsunTinTub8MU9LYhLvky/T9bz05YT/LItlo51PIs3J0vTVFvLESNUi8avvgIHhxI9j6pmfOcQgj0c2RCdwPhOIax7rhsTOofiYGtj6dCEEKJA1v/uMDcXnJwsHYUQopLpE64uNJaVoLps58lkxny7FV9XB+aMb4uXiyTKKrshzQOxszFwV8uC5yFUFD6uDgxqGsDc7bEkpWXy3z8O8OeeM7zUt8G1GRNCCCFEebmzRQDeLvZ8vvpo0RsXIDY5HRuDhp9bMW5Y9uqlWmsF5VNBIMqEwaDx9pDGXMnO5bXFBywdjqJpMHkyTJ2q/n3sGFwu2eK4iiQxTVUjeZb2uqNaNbj99mLNtiqO6o52dGvgxeLdp02rUjIYVHXZypVqPlQxxSalsz46nuGtgrApTtVKYKBqY7hwITg44GRv5N2hTfhsZDOOxqfy0KydeJS0mqmE6ng7M6R5ID9uPsGZC9fPxQ1HEtB1yqVNXce6XtjZGMquFSNcT5hNnqxmhxXT/tMXmLb6CIObBdAjzKfoHf76S7UV/eEHNaNw927o1AlQC2KXP9GZljU9+M+CfZxKuczwVvI7oaw42Now7+H2bHi+Gy/1bVi60RRCCFHOJFkmhBD5qO3pRANfF5btO1Os7XfHpjDmm614utgze3xbvF1llVlV0KqWB3tf60Ujf+toXzihcwhXsnK5Z8YWZm48ztgOtRnfKcTSYQkhhKiC7I02jOtUm00xiUSeLF01Q1zyZfyrO2AsTnW3Ju2eLCHEy5nHb6vLn3vPmDyjzqw0TXWp6dIF+vWD1FRLR1QqCVcryzydSpksW7EC/v7bjBHB4GYBJKRm8M/RRNMO9MorEBMDRmOxd/l520k0Cmird6OkJDWvrW5dVb3m7n7Th/s38Wfp4524o6k/U4c3LV41kwkev60uuq7z6aoj1x5bdzget2q2RARWL9PPDeBsb6RNiAcrojgXTUcAAB9TSURBVMq48tbWVlV2urmp779ffy1086ycXJ79dQ/VHe14dUAxE5bVq0NwsJo39tZbt1R/+bg68MPY1rzcryG9wnyudQoRZcPLxV7ujQghrIoky4QQogB9wv3YfiKZ8xcLbxuz79QFRn+zhepOtswZ3xbf4qxuFpWGvdF62kjU9XHhtgbeHDhzkf5N/Hi5X0M0uXkohBDCQka2qYlbNVs+X1O66rLYpHQCqxejfZawqAmdQ2jg68Iri/Zx8UqWpcO5ztER3nwT1q6Fjh1h7lzIzLR0VCWSmJqB0aDhWq34CaWbvPWWSkqZUbcG3rg6GFmwM860AwUE3JLEKkxWTi5zt8fRrb43/tULmWOYmKjmej35ZKHHC3R3ZOrdzWhfp+znEgd5OHJ3q2DmbovlZGI6uq6zLjqejnU8i1chZwY9GvoQE5/GjPUxJKeVw/fB1KkwbBh8+GGBm3yx5igHzlzkjUHhBVcl6TrMmKFa7QK0bg1btkDTpgUe12DQGNcphK/ubWlV13JCCCHKnvUny4xGtRpICCHMrG9jX3QdlheyCnb/6QuMmrEFFweVKCv0wkyICuCV/mE80aMuHw6LkKHKQgghLMrZ3siYdjX5+8A5Dp+7VOL9Y5MvE+Qh770qOlsbA+/c2YT4Sxm8t+ygpcO52ejRsGABXLgAw4dDrVpq3pGVSEzNpIazXekXP0VFQZh5WwzaG23o18Sf5fvPkZZR/BaK+fr9d5VQ0fUiN10ZdZ74SxmMaB1c8EaXL8PAgar95pAhpsVmZpO618HGoPHxisMcPpfKuYsZdK5X9om6PAMi/GkS6MYbf0bR+q0VPPjjdpbvP0tmtgntNAvz7LNqhtkzz8Drr8OaNSqRCXDqFKdm/MjRT2fw2oWd9N66RM0IO3v1unzvXnj7bVWl1r07jB8PW7deT3bLYkAhhBClVMrlRxVIrVrwyy+WjkIIUQnV9XEh1MuJJXvPMrpdrVs+fvDsRe6ZsQVHOxvmjG9LYHGGywthYbU8nXiiRz1LhyGEEEIAcF+H2ny9/hhfrDnK/4YXXAnwb1eycoi/lEGQvP+yCk2DqnN/h9p8s+EYdzQNoFUtD0uHdN3AgaoV4/LlsGHD9Wqmjz6Cxo3VzXhDxVxnnJiWQY3StmBMTlbJh4YNzRsUqhXjnK0n+evAWQY3M2G2b0KCatX30kuFVgoBzNl6Ej83B7rWL2DGV04OjBgBmzapY3buXPq4yoCPqwNj2tfi6/Ux2F5tLVse88ryeDjZsXhSRw6cvsj8nXEs3HWa5fvP4e5oy8AIf4Y0D6RJoJv5ulIYjTB7tvr35Mnq76VLoXdvcjZtImD8vXyct+0XV/8OCwNfX4iMVOcEgIcHfPkljBtXYb9PhRBCWA/5TSKEEIXo29iPLccSSUzNuOnx6HOXGPX1FuyMBuaMb0twDblRI4QQQghRUh5OdtzdOohFu08Tm5Re7P3iktW2QR7yHsxaPN2rHoHu1Xhh3h4ysnMsHc7NbGygb1/VlhDgyhX44APo2RMaNFCJswpYcZZwtbKsVKKi1N9mriwDaFnTnUD3aszfecq0A/Xrp6qEFi8udLPYpHTWRcczrGVQwTMMn3gCFi2CTz6BO+80La4y8lCXUJzsjPyyPZa63s74uZV/5WyYvysv9w9j84vd+e7+VnSo48mcbbHcMe0fen60js/XHOF0ymXzfDKjEebMgfXrYdUqaNUKgO8cQuh9/6esXbAWoqPh+HGIi1MtFgFGjlTfozk5qhptwgRJlAkhhDAL6/9tcvQovPeepaMQQlRSvcN9ydXh7wPXhx0fOZ/KiK+3YDBozBnfllqeMjdRCCGEEKK0xncKwaDB1+tjir1PbJK6WSttGK2Ho52RNwc35mh8GtNWl25OXblxcICYGJg1C7y84Kmn1AytefMsHdlNElIz8HQuZWXZgQPq7zKoLDMYNAY1DeCfIwlFzn8ulLc3tG1bZLLsl22xaMCwVkEFb9S/P0yZApMmlT6eMubhZMfYjrWB8q0qy4/RxkC3+t58NrI52/7Tg3eGNMbd0Zb3lh2iw7urGDVjM/N3xpneatPGRs0M7NYNatQg+twl3tt0jtrd29FlUGeoUwdq1lTff3ZXE8NGI9jbS4JMCCGE2Vn/b5bUVNVvWgghykCYnyvBHo4s2af6ox9LSGPk15sBnTnj2xDi5WzZAIUQQgghrJx/9WoMahrAL9tiib+UUfQOQGxeZZm0YbQqXep5MbhZANPXHOHQ2ZLPqStX9vYwahT88w/s2qXmm7VooT62YQPMnKlmYFlQYmomnqWtLLv3Xti3T422KAODmgWQq8Pi3adNO9DAgbBjB5zKv0otKyeXudtj6VrfmwAnI8THq0XVu3bBunXqawVw++3w6qumxVIOxnWqTe9GvgxrWUjir5y5VbPl7tbB/PpQe9Y+25XHb6tLbNJlnpq7m1ZvruCpubvYEJ1Ado5p881ycnWe/W0PTvY2/PeOcDNFL4QQQhSf9SfLcnLASao6hBBlQ9M0+jT2ZeORBPbEpTDiq81k5+rMHt+WOt4ulg5PCCGEEKJSeKhrKJk5uXz3T/EWQsYlX8beaMDLpZRVNcJiXukfhouDLc/P20NOrm7pcIonIkLNRcpLLM2aBfffr6pdnnxSJXP08n0u6ZnZXM7KoUZpK8vs7KBRozKrzqnj7UyTQDcWRJrYinHgQOjSRbXb27wZhg2D3r2hQwdo0oTs4Jp4HoliROtglcD09lbVSM2aqf06d4aFC83ynMqDq4MtX4xuQX3finmtWbOGmn+89tmu/PpQO+5o6s/f+89xzzdbaPHGCp78ZRd/7jlDaikqzr7ZEMOu2BSmDGwkP9uFEEJYhPUny3RdkmVCiDLVJ9yP7FydodM3cSU7h5/GtaGeT8W8eBFCCCGEsEahXs70buTLj5tOcPFKVpHbxyalE+heDU3TyiE6YU4eTnZM7h/GrtgUftx03NLhlM706bB6NfToAdOmQcuWqs1fOUpMzQSghlMpK8tefRVWrjRjRLca1DSA/acvcvicCVWEYWGwZg00aaI6C+3dC0lJUK0ahIayo1YTnNxd6VbfSyXQPv0Uvv8e5s+Hv/+GLVvK/WtTFWiaRqtaHrw9pAnbXu7BF/c0p0dDH9YcOs8js3fS/L9/c++3W/lx0/FizTg7Gp/Kh38dpkdDHwZG+Jf9ExBCCCHyYbR0AGYhyTIhRBmKCHQj0L0aFy9nMeuBNjT0c7V0SEIIIYQQlc7ErnVYuu8sszafYGLXOoVuG5ucTqC0YLRadzT1Z0HkKd5ffoiejXwJqG5ls+c0Dbp2VX+Sk9UsM/urlTAZGdCnDwwYAMOHg3/Z3PhPSFUtS0s1sywtDf77X3j9dbjtNjNHdt2ACH/eXBLFgshTPN+7gekH7NEDoqKu/Tc2KZ3R76/m0e51MdoYVGItLMz0zyNKxMHWht7hfvQO9yM7J5edJ1NYEXWOvw+c45VF+3ll0X7CA1zp0dCHHg19aOTvetNCh5xcned+24O90cBbg8NlEYQQQgiLsf7KMkdHCA62dBRCiEpM0zRmPdCGpU90JjzAzdLhCCGEEEJUSo0D3ehU15NvNxzjSlZOodvGJl0myMPKEiziGk3TeHNwODrw8oK96OXcwtCs3N1h3Dg10wzUbK2LF+GppyAwUCWjvvkGLlww66e9VllWmpllBw+qv8s4seTlYk+nup4sijxFbhm03Jy7PRaA4a0qznyvqs5oY6B1bQ9e6tuQVU93YcVTXXihTwPsjTZMXRlN/0830OGdVUxetI91h+PJyM5h5sbj7DiRzKsDGuHt6mDppyCEEKIKs/5kWcOGcPfdlo5CCFHJ1fJ0sr4Vr0IIIYQQVubhrqEkpGby69Wb4Pm5eCWLC5ezCJLKMqsW6O7I073qs/pQPL/vOWPpcMwnJAS2b1cJqcmT4eRJlUw7cEB9PCEBLhfdlq4oiWmqsqxUM8vyYmnY0OQ4ijK4WQCnL1xh6/Eksx43OyeXX7bF0rWel1ynVVCaplHH25mHuoQy7+H2bPtPD94b2oRGAW7M3R7Lvd9upcXrK3h32UG61fdiSPMAS4cshBCiirP+ZJkQQgghhBBCiEqhXUgNmgZV58t1MWTn5Oa7TWxSOgBBHpIss3b3ta9FRKAbry3eT3JapqXDMa/69WHKFDh8WCXP2rZVj0+eDD4+cN99sGQJpKeX6vAJpswsi4oCoxHqFN7u1Bx6hfniZGfDgp2nzHrcVQfPc/5SBiNaS6cha+HpbM+wlkF8fW9Ldk3uxTdjWtK/iR8RgW68NaSxtF8UQghhcdafLDtwADZtsnQUQgghhBBCCCFMpGkaE7uGEpd8md/3nM53m9gkVZUjlWXWz8ag8c6dTbhwOYs3/owqegdrpGnQooX6G2DECLjrLli4EPr1Aw8PuPfeEh82ITUDZ3sjDrY2JY/p9GmoWxdsbUu+bwlVs7Ph9nBfluw9U2R71ZKYs/UkPq72dG/gbbZjivLjYGvDbQ19eOfOJvz6UHv83KQ6UAghhOVZf7Ls8mXIyrJ0FEIIIYQQQgghzKBHQx/qejszfc3RfOccxSXnVZbJzdXKoKGfq2rTtjOODdEJlg6n7HXqpGaYnT0Ly5fDI4+o1o0Aug6tW8P998OcOaplYwESUzPxLM28MoCZM2HnztLtWwqDmwVwKSOblVHnzXK8uOR01hyOZ3jLIIw21n9bSwghhBAVQ+V4V+HkZOkIhBBCCCGEEEKYgcGg8XDXUA6fS2XVwVtvrsclX8bF3ohbtbKvihHlY1L3OoR4OvH8vD3ExKdaOpzy4eAAvXrBhx+qdo0AqalQuzYsWgQjR4K3N7RqBYsX37J7YlpG6eaV3fj5y0n7UE/83RyY8vt+Nh41PSE6d5uaaTisVZDJxxJCCCGEyCPJMiGEEEIIIYQQFcqACH8Cqlfj8zVH0PWbq8tik9IJcK8m820qEQdbGz4cFkFaZjb9PtnAL9tO3vJ1rxJcXOCXXyA+HrZsgddeA3v76y0cd++GQYNg+nScjhzGy6EUt3QOH4ahQ2HvXvPGXggbg8a397fCxcHIPTO2MHVFNDn5VI0WR3ZOLr9sj6VLPS8CpRWrEEIIIcxIkmVCCCGEEEIIISoUWxsDD3YJYefJFLYcS7rpY7HJ6QR5yE3yyqZZsDvLHu9Ms+DqPD9vLxN/2klKeqalw7IMGxvVjvGVV2DDBhgwQD1++jTs2gUTJ/LVu2P4bEJnaNoUYmLUx8+cgdhY1c6xILt2wbx5kGO++WHF0cDXld8ndeSOpgF8tOIwo7/ZwvlLV0p8nNWH4jl3MYMRrYPLIEohhBBCVGXWnyxzcQFXV0tHIYQQQgghhBDCjIa1DMLT2Y7P1xy99piu68QmXSZIKkoqJV83B2Y90IYX+jTg7wPn6DN1PZuOJlo6rIqjTx84dozcA1E83e9JIgffC35+ql0jwCefQHAwuLtDx47w8MPw+eeQnX39GFFRqlKtfv1yD9/J3sj/hkXw3p1N2Hkymb5TN7DxSMnaMs7ZehJvF3tua+BdRlEKIYQQoqqy/mRZvXrg5mbpKIQQQgghhBBCmJGDrQ33d6jNusPx7Dt1AYDEtEwuZ+UQ5FHNwtGJsmIwaDzUJZQFEzvgYGvDyBmbeW/ZQbJyci0dWsWgaaQEhzAv/Db2P/4fWLoUnJ3Vx0aNUsmxkSPBYICff4b//EdVqgE8/TRMn67molWzzPeQpmkMaxXEokc64lbNyKhvtvC/vw8Xqy3jqZTLrDl0nuGtgjDaWP/tLCGEEEJULPLuQgghhBBCCCFEhTS6XU1c7I1Mv1pdFpuUDiCVZVVA40A3/ni0I8NaBPH5mqMMnb6R4wlplg6rQkhIzQCghrP9zR8ID79eTbZuHSQlQXT09Zlnzs7g76+SahZW39eFxZM6MrhZAJ+sjOaeGVs4f7Hwtoy/bItFR1WdCiGEEEKYm/Unyw4csHQEQgghhBBCCCHKgKuDLfe0q8mSfWeIiU8lNvkygMwsqyKc7I28O7QJ00c153hiOn0/Wc/c7bHohc3kqgLykmWe/06W/Zumgafn9f+/9hrs3An//W8ZRld8qi1jU94f2oTI2GT6frKeDdH5t2XMzsll7rZYOtf1ku9/IYQQQpQJ60+W3dh7WwghhBBCCCFEpTK2Q23sbAx8uTaGuGRVWRboLm0Yq5I+jf1Y+ngnmgS68dxve5g0O5IL6VmWDstiElMzAfB0trNwJOZxV8sgFk/qiLujHaO/3cKHfx0i+19tN9cciufsxSuMaB1soSiFEEIIUdmVSbJM0zQHTdP+0DRtt6ZpP2paXs1/4dsUZ79bn4H15/uEEEIIIYQQQuTPy8WeYS2DmB8Zx/bjydRwssPJ3mjpsEQ5869ejZ/GteW53vVZvv8sfaauY0tMoqXDsojEgtowWrF6Pi4smtSBoc0D+XTVEUbN2MK5G9oyztl6Em8Xe25r6G3BKIUQQghRmZVVpukeIE7X9QjAHehZzG2Ks9/NJFkmhBBCCCGEEJXahM4h5Oqw6uB5qSqrwmwMGhO71mHew+2xMxoY8fVmPlh+iKx/VSFVdolpmRg0qF7N1tKhmJWjnZH374rgg7si2BN3gb5T17PucDynUy6z+tB5hrUMwtZG7gEJIYQQomyU1XK87sC8q/9eBXQD/irGNjWLsd/NJFkmhBBCCCGEEJVakIcjAyP8WRB5ikCZV1TlRQRV58/HOjFl8X4+W32EDUcSePfOJni7VJ5Kq8KcTrmCh5M9BkPRzXis0dAWgUQEuvHI7J2M+W4rYX6u6MDwVkGWDk0IIYQQlVhZJctqABeu/vsiUL+Y2xRnv5u5upoSpxBCCCGEEEIIK/Bw11AWRJ6iVg1JlglwsldVSF3qe/Hi/L3c/vE6S4dUrsL8Kve9kLo+Lix6pCOvLt7H3O1xdK7nRZAkyoUQQghRhsoqWZYAuF39t9vV/xdnG+di7IemaROACQDBwTLcVQghhBBCCCEqu3o+Lswe14b6vi6WDkVUIP2b+NM82J2VUefIydUtHU65aV7T3dIhlLlqdja8NzSCQc0CCPF0tnQ4QgghhKjkNF03/5tJTdPGAm10XX9Q07Q/gY90XV9R1DZAcFH7/VvLli317du3m/05CCGEEEIIIYQQQgghhBBCiIpN07Qduq63NOUYZTXw6ycgQNO0PUAScFTTtA+K2GZlAY8JIYQQQgghhBBCCCGEEEIIUSbKpA2jrusZQP9/PfxMMbbJ7zEhhBBCCCGEEEIIIYQQQgghykRZVZYJIYQQQgghhBBCCCGEEEIIUeFJskwIIYQQQgghhBBCCCGEEEJUWZIsE0IIIYQQQgghhBBCCCGEEFWWJMuEEEIIIYQQQgghhBBCCCFElSXJMiGEEEIIIYQQQgghhBBCCFFlSbJMCCGEEEIIIYQQQgghhBBCVFmSLBNCCCGEEEIIIYQQQgghhBBVliTLhBBCCCGEEEIIIYQQQgghRJUlyTIhhBBCCCGEEEIIIYQQQghRZUmyTAghhBBCCCGEEEIIIYQQQlRZkiwTQgghhBBCCCGEEEIIIYQQVZYky4QQQgghhBBCCCGEEEIIIUSVJckyIYQQQgghhBBCCCGEEEIIUWVpuq5bOgaTaJoWD5wo5e5uwAUzhlMePIEESwdRQtb2OltbvGCdMcu5XD4k5rIn53L5kJjLh5zP5cPaYra2eEHO5fIiMZcPazufrfE1lpjLh7Wdy2Cdr7O1xWxt8YKcy+VFYi4f1nY+W+NrLDGXj/q6rruYcgCjuSKxFF3XvUq7r6ZpX+m6PsGc8ZQ1TdO267re0tJxlIS1vc7WFi9YbcxyLpcDibnsyblcPiTm8iHnc/mwtpitLV6Qc7m8SMzlw9rOZyt9jSXmcmBt5zJY7etsVTFbW7wg53J5kZjLh7Wdz1b6GkvM5UDTtO2mHqOqt2H83dIBVBHW9jpbW7xgnTFbI2t8nSVmkR9rfI0lZlEQa3ydrS1ma4vXWlnj6ywxi/xY42ssMYuCWOPrbG0xW1u81soaX2eJWeTHGl9jidlKWH0bxqrG2rL9QhREzmVRWci5LCoTOZ9FZSHnsqhM5HwWlYWcy6KykHNZVCZyPovKwhznclWvLLNGX1k6ACHMRM5lUVnIuSwqEzmfRWUh57KoTOR8FpWFnMuispBzWVQmcj6LysLkc1kqy4QQQgghhBBCCCGEEEIIIUSVJZVlQgghhBBCCCGEEEIIIYQQosqSZFkFomna95qmbdY0bbGmac6apv2hadpuTdN+1DRNu7qNraZpvxeyn9Ey0Qtxs9Kcz5qmGTVN+1XTtH80TfvWctELcV1pfzZfffwpTdNWlH/UQtyqlD+XW2maFqdp2oarf+pb7hkIcZ0J75ufu7rfUk3T7CwTvRDXlfJnc9cbfi7Hapo2xnLPQAillOeyk6Zpi65e/71nueiFuFkpz2d3TdPWXD2fX7Fc9EJcV8xz+ab7ypqmOeS3nRCWVJpz+epj+d6vK4gkyyoITdM6AkZd19sCrsBYIE7X9QjAnf+3d38hcp1lHMe/v8YQExJilBZrFf/QG0kJwdqbNq1pNYLQFv8glLUoRm8EUbAU6YVQ8MILUVEiemNBUPCm9KahRqMGFdNWQpNUi0WtIoJa26KxatqYPF7MWd1sZmZnz3HOzDrfDyyc3Xnf4Vn4MZxznvO+AweSbAVOAAfGzHt778VLq7TNM/BO4FRV3QBcmWRvz6VLF+mQZZK8FvDmleZChyzvAr5SVfuanyf7rl1arcN58xuA3c28h4BX9168tELbLFfVseXPZeA08Fj/1Uv/1eE8433Aw8313+4kb+y5dOkSHfK8BPy8yfMNSV7fc+nSRSbM8rD7yneuHjeTf0BqtM3yqPt149gsmx9/Ar7YHF8G3At8t/n9+8DNVfXPqtoD/H7MPGketM3zt4HPN93/lwFn+ilXGqltlmnm3dNHkdIE2mZ5F/CeJI8mud+nCjUn2ub5rcCuJD8EbgR+00+50khdzjNIsg24uqpO91CrNE7bLP8F2J5kE7AVeLGfcqWx2uY5wI7mfDmAD/9q1tbM8pAxALcMGSfNUqssjzuPHsUt++ZEVf0SIMm7gAsMng78a/PyGWDotkdD5n1n6sVKa+iQ5+ebeY8Af6iqp6ZfrTRa2ywnWQJOAU/0UKa0prZZBn4FfKqqDif5CfAW4Nh0q5XG65Dny4E/V9XtSY4D+4AfTblcaaQOWV52APje1AqUJtQhyw8An2SwwuxwVf16yqVKa+qQ528wWJVzP/ACgwawNDOTZHnEfeWPrx7XY9nSJTpked1ciTRHktwOfAy4DfgjsLN5aSfwzCTzqupf065TmkSbPCd5RZItwPUMnvz26RXNXMvP5lsZrGD4FnBtko9Ou05pLS2z/Fvg6IrjK6ZXoTS5lnk+AyxvJfoUcNU0a5Qm0fYasHEb8OD0qpMm1zLL9zDY7vl1wMuTXD/tOqVJdPhs/lBVvZtBs+zpqRYpTWCSLA+5r/zMsHHSLLXM8rrZLJsTSV4J3A3cWlV/Y/CE4PL3j90C/GDCedLMtc0zcBfw3qo6D/wDn8TSjLXNclUtNd8jcgdwoqoO9VGvNEqHz+VPAHckuQy4BvjZtGuV1tIhzyeANzfHVzNomEkz0yHLNNt87Wew9Yw0Ux2yvAM42xy/AGyfZp3SJDrk+Sbgq80DwHuBh6ddqzTOJFkecV954vMRqQ8dsrxuNsvmxweAK4EjSX4MbAauSnIaeI7R22tcNC/JwV6qlcZrm+cvAwebrZGeBY70Uaw0RtssS/OmbZYPAR8EHgEeqCq3FtU8aJXnqjoOPJvkp8CTVfVoXwVLI3Q5z7gOeKKqzo4ZI/Wly/XfR5rrv61jxkl9apvnh4CXMtji+dPLXzMhzdAkWR52X/mbQ8ZJs9Q2y+uWqvof1SxJkiRJkiRJkiRtLK4skyRJkiRJkiRJ0sKyWSZJkiRJkiRJkqSFZbNMkiRJkiRJkiRJC8tmmSRJkiRJkiRJkhaWzTJJkiRJ+j+Q5GAGNifxWk+SJEmSJvSSWRcgSZIkSVq/JPcBX6qqk82floAArwJuTHKh+fv2qto3ixolSZIkaSOwWSZJkiRJcyrJJuA54DFgL3B5VZ1rXn4ROLdi+L3A5qr62qr3ONxDqZIkSZK0Ybk1hyRJkiTNqao6DzxeVfuBk8CdST6X5DPAtcBdSd6U5AhwHHhHkqPNz9eX32YmxUuSJEnSBuHKMkmSJEmab9ckOcZgZdnNwGuq6ndJdgCHquoXSc5V1fkku6vqbeCKMkmSJEmalM0ySZIkSZpvp6pqf9Mw2wYcTnLdiLGV5GhzvLOX6iRJkiRpg7NZJkmSJEnz7T/b51fV35PcB+wZNXjFyrIHe6hNkiRJkjY8m2WSJEmSNN/2LG/DmGRTVX0BIMn7h4zdsmJl2RV9FShJkiRJG5nNMkmSJEmaU0k2AY832zDevfrl1cdVdWDV/LBiZZokSZIk6VJeNEmSJEnSnKqq88BSc/zZ5neSfBi4CXi6GbolyeaVc5tG2QngZH8VS5IkSdLGk6qadQ2SJEmSpHVIsg04W1UX1hi3vaqe76ksSZIkSdqQbJZJkiRJkiRJkiRpYbkNoyRJkiRJkiRJkhaWzTJJkiRJkiRJkiQtLJtlkiRJkiRJkiRJWlg2yyRJkiRJkiRJkrSwbJZJkiRJkiRJkiRpYf0bnTm2r6njckMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 2160x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# 美吉姆预测结果显示\n",
    "plt.figure(figsize=(30,7))\n",
    "data_month['成交金额'].plot(label='实际成交金额')\n",
    "data_month['预测成交金额'].plot(color='r', ls='--', label='成交金额')\n",
    "plt.legend()\n",
    "plt.title('美吉姆成交金额（月）')\n",
    "plt.xlabel('时间')\n",
    "plt.ylabel('成交金额')\n",
    "plt.show()\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
